Biology subjects

Lutz, S.

Publications and source records attributed to Lutz, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Disturbed mitochondrial energy production in methylmalonic aciduria is cell-type and variant-dependent

Methylmalonic aciduria (MMA) is caused by deficiency of methylmalonyl-CoA mutase (MMUT), which catalyses the final step of propionate catabolism and fuels the tricarboxylic acid cycle for energy production. Previous studies reported disrupted mitochondrial homeostasis in MMA, including reduced mitochondrial membrane potential and increased oxidative stress, especially in energetically demanding and chronically affected tissues like brain and kidneys. However, how these changes impact mitochondrial energy production remains unclear. Here, we systematically investigated mitochondrial energy production using extracellular flux analysis in cellular models of MMA, including 293T cells, patient-derived fibroblasts, urine-derived epithelial kidney cells and induced pluripotent stem cells (iPSCs) as well as iPSC-derived neurons harbouring either complete loss (knockout, KO) or pathogenic missense variants in MMUT. We found no impact on mitochondrial energy production in MMUT-KO 293T cells and fibroblasts compared to controls. In contrast, fibroblasts and 293T cells expressing the pathogenic MMUT-p.N219Y variant showed decreased energy production. This corresponds to the altered mitochondrial membrane potential in 293T cells, but contrasts with their unchanged mitochondrial abundance. Depletion of glucose, glutamine and pyruvate from the media or provision of each individually as sole fuel source exacerbated the phenotype of MMUT-p.N219Y clones, but did not induce a phenotype in MMUT-KO 293T cells. Finally, we confirmed reduced mitochondrial energy production in patient-derived kidney cells but found no evidence in MMUT-p.N219Y iPSCs and their derived neurons. Overall, our work suggests that the impact of MMUT-deficiency on mitochondrial energy production is cell type- and variant-dependent. Further investigations should clarify molecular mechanisms and their clinical impact.

cell biology↗

bioRxiv2025

High-resolution, genotype-free mapping of genetic variation with CRI-SPA-Map

Genetic variation within species shapes phenotypes, but identifying the specific genes and variants that cause phenotypic differences is costly and challenging. Here, we introduce CRI-SPA-Map, a genetic mapping strategy combining CRISPR-Cas9 genome engineering, selective ploidy ablation (SPA), and high-throughput phenotyping for precise genetic mapping with or without genotyping in the yeast Saccharomyces cerevisiae. In CRI-SPA-Map, a donor strain carrying SPA machinery is mated to a genetically different recipient strain harboring a genome-integrated selectable cassette. In the resulting diploid, CRISPR-Cas9 cuts the cassette for replacement with DNA from the homologous donor chromosome. Donor chromosomes are then removed using SPA to yield haploid recombinant strains. To establish CRI-SPA-Map, we mated a W303 SPA strain to 92 strains from the BY4742 yeast knockout collection that carry gene deletion cassettes on the left arm of chromosome XIV and created 1,451 recombinant isolates. Whole-genome sequencing verified that deletion cassette replacement introduced short donor DNA tracts of variable length, resulting in a finely recombined mapping population. Using only the known location of the gene deletions, which marks where donor DNA is introduced, we identified a 6.5 kb-region shaping yeast growth. Further dissection of this region pinpointed two causal variants in two genes, MKT1 and SAL1. Engineering these variants alone and in combination revealed gene-by-environment interactions at both genes, as well as epistatic interactions between them that were in turn dependent on the environment. CRI-SPA-Map is a cost-effective strategy for creating high-resolution recombinant panels of yeast strains for identifying the genetic basis of phenotypic variation.

genetics↗

bioRxiv2025

Cardiac fibrosis inhibitor CTPR390 prevents structural and morphological changes in collagen and fibroblasts of engineered human connective tissue

Cardiac fibrosis is a key characteristic of heart failure, with no effective treatment available. Using three-dimensional human models and cutting-edge biotechnology to evaluate new therapies offers a significant advancement. CTPR390, an experimental anti-fibrotic inhibitor targeting Hsp90, has shown success in animal models, but remains unexplored in human cardiac models. This study evaluated a cardiac three-dimensional engineered connective tissue (ECT) model treated with CTPR390, focusing on changes in the extracellular matrix and fibroblasts. Results showed that CTPR390 prevented architectural changes in TGF{beta}1-activated ECT, preserving tissue perimeter, collagen fibers alignment while reducing percentage of structured areas and degree of collagen structuration. Additionally, the treatment reduced cell area of elongated fibroblasts under tension, without changes in the internal rounded cells devoid of tension. Fibroblast recruitment to tension areas was diminished, showing biomechanical behavior similar to control ECT. This treatment also lowered the gene and protein expression of key pro-fibrotic markers. For the first time, advanced biotechnology was employed to detect the detailed structure of tissue fibrosis reduction after administering CTPR390, representing a significant advancement toward clinical application for cardiac fibrosis treatment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=56 SRC="FIGDIR/small/633162v2_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@1f84961org.highwire.dtl.DTLVardef@19999eeorg.highwire.dtl.DTLVardef@1491286org.highwire.dtl.DTLVardef@5f2968_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

Hydrophilic/ Omniphobic droplet arrays for high-throughput and quantitative enzymology

Engineered enzymes with enhanced or novel functions are specific catalysts with wide-ranging applications in industry and medicine. Here, we introduce Droplet Array Microfluidic Enzyme Kinetics (DA-MEK), a high-throughput enzyme screening platform that combines water-in-air droplet microarrays formed on patterned superhydrophilic/omniphobic surfaces with cell-free protein synthesis to enable cost-effective expression and quantitative kinetic characterization of enzyme variants. By printing DNA templates encoding enzyme variants onto hydrophilic spots, stamping slides to add cell-free expression mix, and imaging the resulting arrays, we demonstrate reproducible expression of hundreds of enzyme variants per slide. Subsequent stamping of fluorogenic substrates and time-lapse imaging allows determination of Michaelis-Menten parameters for each variant, with measured catalytic efficiencies spanning 5 orders of magnitude and agreeing well with values obtained via traditional microtiter plate assays. DA-MEK consumes orders of magnitude less reagents than plate-based assays while providing accurate and detailed kinetic information for both beneficial and deleterious mutations. In future work, we anticipate DA-MEK will provide a powerful and versatile platform to accelerate enzyme engineering and enable screening of large variant libraries under diverse conditions.

bioengineering↗

bioRxiv2024

Evolving a High-Performance Terminal Deoxynucleotidyl Transferase for Enzymatic DNA Synthesis

Enzymatic DNA synthesis, using stepwise nucleotide addition catalyzed by template-independent polymerases, promises higher efficiency, quality, and sustainability than todays industry standard phosphoramidite-based processes. We report on the directed evolution of a terminal deoxynucleotidyl transferase that uses 3-phosphate blocked dNTPs to control the polymerization reaction and demonstrates high activity for these modified substrates and improved template promiscuity and thermostability.

bioengineering↗

bioRxiv2024

Polygenic hazard score models for the prediction of Alzheimer's free survival using the lasso for Cox's proportional hazards model

The prediction of the susceptibility of an individual to a certain disease is an important and timely research area. An established technique is to estimate the risk of an individual with the help of an integrated risk model, that is a polygenic risk score with added epidemiological covariates. However, integrated risk models do not capture any time dependence, and may provide a point estimate of the relative risk with respect to a reference population. The aim of this work is twofold. First, we explore and advocate the idea of predicting the time dependent hazard and survival (defined as disease free time) of an individual for the onset of a disease. This provides a practitioner with a much more differentiated view of the absolute survival as a function of time. Second, to compute the time dependent risk of an individual, we use published methodology to fit a Coxs proportional hazard model to data from a genetic SNP study of time to Alzheimers disease (AD) onset, using the lasso to incorporate further epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status, ten leading principal components, and selected genomic loci. We apply the lasso for Coxs proportional hazards to a dataset of 6792 AD patients (composed of 4102 cases and 2690 controls) and 87 covariates. We demonstrate that fitting a lasso model for Coxs proportional hazards allows one to obtain more accurate survival curves than with state-of-the-art (likelihood-based) methods. Moreover, the methodology allows one to obtain personalized survival curves for a patient, thus giving a much more differentiated view of the expected progression of a disease than the view offered by integrated risk models. The runtime to compute personalized survival curves is under a minute for the entire dataset of AD patients, thus enabling it to handle datasets with 60, 000 to 100, 000 subjects in less than one hour.

bioinformatics↗

bioRxiv2024

High-throughput Tn-seq screens identify both known and novel Pseudomonas putida KT2440 genes involved in metal resistance

Chemical waste with toxic effects is released into the environment by industrial and urban activities. Pseudomonas putida, a rhizosphere bacterium, harbors a wide variety of genes capable of degrading hydrocarbons and xenobiotic compounds in its natural environment. This bacterium harbors also a large set of metal resistance genes. Most studies that identify genes involved in metal resistance in P. putida focus on over/underexpressed genes and may miss other genes important for metal resistance whose expression does not change. In this study, we used a Tn-seq approach to determine the essential genome of P. putida required for growth in the presence of an excess of metals in a culture medium. Tn-seq enables the detection of mutants with reduced or increased fitness in the presence of metal excess. We validated our screen by identifying known metal resistance gene such as czcA-1 (PP_0043), cadA-3 (PP_5139), cadR (PP_5140) and pcoA2 (PP_5380). Their mutants were underrepresented in the presence of zinc, cadmium (for cadA-3 and cadR) or copper respectively. In this study, we demonstrate by targeted mutagenesis and complementation assay that PP_5337 and PP_0887 are putative transcriptional regulators involved in copper and cadmium resistance, respectively, in P. putida. The study revealed the role of two genes, PP_1663 and PP_5002, in cadmium and cobalt resistance respectively. This is the first evidence linking these genes to metal resistance and highlights the incomplete understanding of metal resistance mechanisms in P. putida.

microbiology↗

bioRxiv2023

The Hidden Biocatalytic Potential of the Old Yellow Enzyme Family

The rapid advancement of sequencing technology has created an immense reservoir of protein sequence-function information that has yet to be fully utilized for fundamental or biocatalytic applications. For example, ene reductases from the old yellow enzyme (OYE) family catalyze the asymmetric hydrogenation of activated alkenes with enhanced stereoselectivity - key transformations for sustainable production of pharmaceutical and industrial synthons. Despite the proven biocatalytic application, the OYE family remains relatively underexplored with only 0.1% of identified members having any experimental characterization. Here, a platform of integrated bioinformatics and synthetic biology techniques was employed to systematically organize and screen the natural diversity of the OYE family. Using protein similarity networks, the known and unknown regions of the >115,000 members of the OYE family were broadly explored to identify phylogenetic and sequence-based trends. From this analysis, 118 novel enzymes were characterized across the family to broadly explore and expand the biocatalytic performance and substrate scope of known OYEs. Over a dozen novel enzymes were identified exhibiting enhanced catalytic activity or altered stereospecificity. Beyond well-established ene reduction, we detected widespread occurrence of oxidative chemistry amongst OYE family members at ambient conditions. Crystallography studies of selected OYEs yielded structures for two enzymes, contributing to a better understanding of their unique performance. Their structures revealed an unusual loop conformation within a novel OYE subclass. Overall, our study significantly expands the known functional and chemical diversity of OYEs while identifying superior biocatalysts for asymmetric reduction and oxidation.

biochemistry↗

bioRxiv2023

Adaptation of Graph Convolutional Neural Networks and Graph Layer-wise Relevance Propagation to the Spektral library with application to gene expression data of Colorectal Cancer patients

MotivationColorectal Cancer has the second-highest mortality rate worldwide, which requires advanced diagnostics and individualized therapies to be developed. Information about the interactions between molecular entities provides valuable information to detect the responsible genes driving cancer progression. Graph Convolutional Neural Networks are able to utilize the prior knowledge provided by interaction networks and the Spektral library adds a performance increase in contrast to standard implementations. Furthermore, machine learning technology shows great potential to assist medical professionals through guided clinical decision support. However, the deep learning models are limited in their application in precision medicine due to their lack to explain the factors contributing to a prediction. Adaption of the Graph Layer-Wise Relevance Propagation methodology to graph-based deep learning models allows to attribute the learned outcome to single genes and determine their relevance. The resulting patient-specific subnetworks then can be used to identify potentially targetable genes. ResultsWe present an implementation of Graph Convolutional Neural Networks using the Spektral library in combination with adapted functions for Graph Layer-Wise Relevance Propagation. Deep learning models were trained on a newly composed large gene expression dataset of Colorectal Cancer patients with different molecular interaction networks as prior knowledge: Protein-protein interactions from the Human Protein Reference Database and STRING, and pathways from the Reactome database. Our implementation performs comparably with the original implementation while reducing the computation time, especially for large networks. Further, the generated subnetworks are similar to those of the initial implementation and reveal possible, and even more distant, biomarkers and drug targets. AvailabilityThe implementation details and corresponding dataset including their visualizations can be found at https://github.com/frankkramer-lab/spektral-gcnn-glrp-on-crc-data Contactsebastian.lutz@uni-a.de

bioinformatics↗

bioRxiv2022

Pantothenate auxotrophy in a naturally occurring biocontrol yeast

The genus Hanseniaspora is characterized by some of the smallest genomes among budding yeasts. These fungi are primarily found on plant surfaces and in fermented products and represent promising biocontrol agents against notorious fungal plant pathogens. In this work, we identify a Hanseniaspora meyeri isolate that shows strong antagonism against the plant pathogen Fusarium oxysporum as a pantothenate auxotroph. Furthermore, strong biocontrol activity in vitro required both pantothenate and biotin in the growth medium. We show that the H. meyeri isolate APC 12.1 can obtain the vitamin from plants and other fungi. The underlying reason for the auxotrophy is the lack of key pantothenate biosynthesis genes, but at least six genes encoding putative pantothenate transporters are present in the genome. By constructing and using a Saccharomyces cerevisiae reporter strain, we identified one Hanseniaspora transporter, out of the six candidate proteins, that conferred pantothenate uptake activity to S. cerevisiae. Pantothenate auxotrophy is rare and has only been described in a few bacteria and in S. cerevisiae strains that were isolated from sake. Such auxotrophic strains may seem an unexpected and unlikely choice as potential biocontrol agents, but they may be particularly competitive in their ecological niche and their specific growth requirements are an inherent biocontainment strategy preventing uncontrolled growth in the environment. Auxotrophic strains such as the H. meyeri isolate APC 12.1 may thus represent a new strategy for developing biocontrol agents that will be easier to register than prototrophic strains, which are normally used for such applications. Significance StatementAs a precursor of the essential coenzyme CoA, pantothenate is present in all organisms. Plants, bacteria and fungi are known to synthesize this vitamin, while animals must obtain it through their diet. Pantothenate auxotrophy has not been described in naturally occurring, environmental fungi and is an unexpected property for an antagonistic yeast. Here, we report that yeasts from the genus Hanseniaspora lack key enzymes for pantothenate biosynthesis and identify a transporter responsible for the acquisition of pantothenate from the environment. Hanseniaspora isolates are strong antagonists of fungal plant pathogens. Their pantothenate auxotrophy is a natural biocontainment feature that could make such isolates interesting candidates for new biocontrol approaches and allow easier registration as plant protection agents compared to prototrophic strains.

microbiology↗

bioRxiv2022

Fast computation of principal components of genomic similarity matrices

The computation of a similarity measure for genomic data, for instance using the (genomic) covariance matrix, the Jaccard matrix, or the genomic relationship matrix (GRM), is a standard tool in computational genetics. The principal components of such matrices are routinely used to correct for biases in, for instance, linear regressions. However, the calculation of both a similarity matrix and its singular value decomposition (SVD) are computationally intensive. The contribution of this article is threefold. First, we demonstrate that the calculation of three matrices (the genomic covariance matrix, the weighted Jaccard matrix, and the genomic relationship matrix) can be reformulated in a unified way which allows for an exact, faster SVD computation. An exception is the Jaccard matrix, which does not have a structure applicable for the fast SVD computation. An exact algorithm is proposed to compute the principal components of the genomic covariance, weighted Jaccard, and genomic relationship matrices. The algorithm is adapted from an existing randomized SVD algorithm and ensures that all computations are carried out in sparse matrix algebra. Second, an approximate Jaccard matrix is introduced to which the fast SVD computation is applicable. Third, we establish guaranteed theoretical bounds on the distance (in L2 norm and angle) between the principal components of the Jaccard matrix and the ones of our proposed approximation, thus putting the proposed Jaccard approximation on a solid mathematical foundation. We illustrate all computations on both simulated data and data of the 1000 Genome Project, showing that the approximation error is very low in practice.

bioinformatics↗

bioRxiv2022

Male sex hormone and reduced plakoglobin jointly impair atrial conduction and cardiac sodium currents

Androgenic anabolic steroids (AAS) are commonly abused by young men. Male sex associates with earlier manifestation of common and rare cardiac conditions including atrial fibrillation and arrhythmogenic right ventricular cardiomyopathy (ARVC). Clinical data suggest an atrial involvement in ARVC. The disease is caused by desmosomal gene defects such as reduced plakoglobin expression. Analysis of clinical records from 146 ARVC patients identified male preponderance and increased prevalence of atrial arrhythmias in patients with definite ARVC. Definite patients displayed ECG changes suggesting atrial remodelling. To study mechanisms of atrial remodelling due to desmosomal vulnerability and AAS, young adult male mice, heterozygously deficient for plakoglobin (Plako+/-) and wildtype (WT) littermates, were chronically exposed to 5-dihydrotestosterone (DHT) or placebo. DHT increased atrial expression of pro-hypertrophic, fibrotic and inflammatory transcripts. DHT caused atrial conduction slowing, decreased peak sodium current density, reduced action potential amplitude and lowered the peak depolarisation rate in Plako+/- but not WT atria. Super-resolution microscopy revealed a reduction in Nav1.5 clustering in Plako+/- atrial cardiomyocytes following DHT exposure. These data reveal that AAS combined with plakoglobin deficiency cause pathological atrial electrical remodelling in young male hearts. AAS abuse may increase the risk of atrial myopathy in males with desmosomal gene variants.

molecular biology↗

bioRxiv2022

Omicron breakthrough infection drives cross-variant neutralization and memory B cell formation

Omicron is the evolutionarily most distinct SARS-CoV-2 variant (VOC) to date and displays multiple amino acid alterations located in neutralizing antibody sites of the spike (S) protein. We report here that Omicron breakthrough infection in BNT162b2 vaccinated individuals results in strong neutralizing activity not only against Omicron, but also broadly against previous SARS-CoV-2 VOCs and against SARS-CoV-1. We found that Omicron breakthrough infection mediates a robust B cell recall response, and primarily expands preformed memory B cells that recognize epitopes shared broadly by different variants, rather than inducing new B cells against strictly Omicron-specific epitopes. Our data suggest that, despite imprinting of the immune response by previous vaccination, the preformed B cell memory pool has sufficient plasticity for being refocused and quantitatively remodeled by exposure to heterologous S protein, thus allowing effective neutralization of variants that evade a previously established neutralizing antibody response. One Sentence SummaryBreakthrough infection in individuals double- and triple-vaccinated with BNT162b2 drives cross-variant neutralization and memory B cell formation.

immunology↗

bioRxiv2021

The influence of unmeasured confounding on the MR Steiger approach

The Mendelian Randomization (MR) Steiger approach is used to determine the direction of a possible causal effect between two phenotypes [1]. For two phenotypes, denoted phenotype 1 and 2, the MR Steiger approach is composed of two parts: (1) MR is performed for a set of single nucleotide polymorphisms (SNPs) that serve as instrumental variables for phenotype 1 and (2) the difference of two correlations, the correlation between the SNPs and phenotype 1 and the correlation between the SNPs and phenotype 2, is calculated. These two parts are then used to determine the direction of a possible causal effect between the two phenotypes. The original MR Steiger paper [1] shows that unmeasured confounding of the two phenotypes affects the validity of the MR Steiger approach, but does not elucidate as to how this occurs. In particular, it was argued that if the magnitude of the observational variance explained between the two phenotypes is above 0.2, the MR Steiger method may return the incorrect causal direction due to unmeasured confounding. This may initially seem surprising since unmeasured confounding does not induce spurious associations between the SNP and phenotype 2, as we demonstrate using directed acyclic graphs. In this note, we show that this is because unmeasured confounding may rescale the magnitude of a non-zero association, and thereby distort the comparison of the correlation between the SNP and phenotype 2 and the correlation between the SNP and phenotype 1. We will end with a number of cautionary remarks on the MR Steiger method, which are partly motivated by this and mentioned in the original MR Steiger paper [1].

genetics↗

bioRxiv2021

Multiple causal DNA variants in a single gene affect gene expression in trans

Identifying the specific causal DNA differences in a genome that contribute to variation in phenotypic traits is a key goal of genetic research. Trans-acting DNA variants that alter gene expression are important sources of genetic variation. Several genes are known to carry single causal variants that affect the expression of numerous genes in trans. Whether these single variants are representative of the architecture of trans-acting variation is unknown. Here, we studied the gene IRA2, which carries variants with broad, trans-acting effects on gene expression in two strains of the yeast Saccharomyces cerevisiae. We found that IRA2 contains at least seven causal nonsynonymous variants. The causal variants were located throughout the gene body and included a pair of neighboring variants with opposing effects that largely canceled each other out. The causal variants showed evidence for non-additive epistatic interactions, in particular among variants at the 5 end of the gene. These results show that the molecular basis of trans-acting variation can involve considerable complexity even within a single gene.

genetics↗

bioRxiv2020

Simultaneous quantification of mRNA and protein in single cells reveals post-transcriptional effects of genetic variation

Trans-acting DNA variants may specifically affect mRNA or protein levels of genes located throughout the genome. However, prior work compared trans-acting loci mapped in studies performed separately or with limited statistical power. Here, we developed a CRISPR-based system for simultaneous quantification of mRNA and protein of a given gene via dual fluorescent reporters in single, live cells of the yeast Saccharomyces cerevisiae. In large populations of recombinant cells from a cross between two genetically divergent strains, we mapped 86 trans-acting loci affecting the expression of ten genes. Less than 20% of these loci had concordant effects on mRNA and protein of the same gene. Most loci influenced protein but not mRNA of a given gene. One such locus harbored a premature stop variant in the YAK1 kinase gene that had specific effects on protein or mRNA of dozens of genes. These results demonstrate complex, post-transcriptional genetic effects on gene expression.One sentence summary A CRISPR-based dual reporter assay enables genetic mapping of DNA variants that specifically affect mRNA or protein levels in trans.Competing Interest StatementThe authors have declared no competing interest.View Full Text

genetics↗

bioRxiv2019

DNA variants affecting the expression of numerous genes in trans have diverse mechanisms of action and evolutionary histories

DNA variants that alter gene expression contribute to variation in many phenotypic traits. In particular, trans-acting variants, which are often located on different chromosomes from the genes they affect, are an important source of heritable gene expression variation. However, our knowledge about the identity and mechanism of causal trans-acting variants remains limited. Here, we developed a fine-mapping strategy called CRISPR-Swap and dissected three expression quantitative trait locus (eQTL) hotspots known to alter the expression of numerous genes in trans in the yeast Saccharomyces cerevisiae. Causal variants were identified by engineering recombinant alleles and quantifying the effects of these alleles on the expression of a green fluorescent protein-tagged gene affected by the given locus in trans. We validated the effect of each variant on the expression of multiple genes by RNA-sequencing. The three variants were strikingly different in their molecular mechanism, the type of genes they reside in, and their distribution in natural populations. While a missense leucine-to-serine variant at position 63 in the transcription factor Oaf1 (L63S) was almost exclusively present in the reference laboratory strain, the two other variants were frequent among S. cerevisiae isolates. A causal missense variant in the glucose receptor Rgt2 (V539I) occurred at a poorly conserved amino acid residue and its effect was strongly dependent on the concentration of glucose in the culture medium. A noncoding variant in the conserved fatty acid regulated (FAR) element of the OLE1 promoter influenced the expression of the fatty acid desaturase Ole1 in cis and, by modulating the level of this essential enzyme, other genes in trans. The OAF1 and OLE1 variants showed a non-additive genetic interaction, and affected cellular lipid metabolism. These results revealed remarkable diversity in the molecular basis of trans-regulatory variation, highlighting the challenges in predicting which natural genetic variants affect gene expression. Author summaryDifferences in the DNA sequence of individual genomes contribute to differences in many traits, such as appearance, physiology, and the risk for common diseases. An important group of these DNA variants influences how individual genes across the genome are turned on or off. In this paper, we describe a strategy for identifying such "trans-acting" variants in different strains of bakers yeast. We used this strategy to reveal three single DNA base changes that each influences the expression of dozens of genes. These three DNA variants were very different from each other. Two of them changed the protein sequence, one in a transcription factor and the other in a sugar sensor. The third changed the expression of an enzyme, a change that in turn caused other genes to alter their expression. One variant existed in only a few yeast isolates, while the other two existed in many isolates collected from around the world. This diversity of DNA variants that influence the expression of many other genes illustrates how difficult it is to predict which DNA variants in an individuals genome will have effects on the organism.

genetics↗

bioRxiv2018

Genetic, structural, and functional analysis of mutations causing methylmalonyl-CoA epimerase deficiency

Human methylmalonyl-CoA epimerase (MCEE) catalyzes the interconversion of D-methylmalonyl-CoA and L-methylmalonyl-CoA in propionate catabolism. Autosomal recessive mutations in MCEE reportedly cause methylmalonic aciduria (MMAuria) in eleven patients. We investigated a cohort of 150 individuals suffering from MMAuria of unknown origin, identifying ten new patients with mutations in MCEE. Nine patients were homozygous for the known nonsense mutation p.Arg47* (c.139C>T), and one for the novel missense mutation p.Ile53Arg (c.158T>G). To understand better the molecular basis of MCEE deficiency, we mapped p.Ile53Arg, and two previously described patient mutations p.Lys60Gln and p.Arg143Cys, onto our 1.8 [A] structure of wild-type (wt) human MCEE. This revealed potential dimeric assembly disruption by p.Ile53Arg, but no clear defects from p.Lys60Gln or p.Arg143Cys. Functional analysis of MCEE-Ile53Arg expressed in a bacterial recombinant system as well as patient-derived fibroblasts revealed nearly undetectable soluble protein levels, defective globular protein behavior, and using a newly developed assay, lack of enzymatic activity - consistent with misfolded protein. By contrast, soluble protein levels, unfolding characteristics and activity of MCEE-Lys60Gln were comparable to wt, leaving unclear how this mutation may cause disease. MCEE-Arg143Cys was detectable at comparable levels to wt MCEE, but had slightly altered unfolding kinetics and greatly reduced activity. We solved the structure of MCEE-Arg143Cys to 1.9 [A] and found significant disruption of two important loop structures, potentially impacting surface features as well as the active-site pocket. These studies reveal ten new patients with MCEE deficiency and rationalize misfolding and loss of activity as molecular defects in MCEE-type MMAuria.

biochemistry↗