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Stein, A.

Publications and source records attributed to Stein, A..

45 records · Page 3Linked to original sources

Understanding the origins of loss of protein function by analyzing the effects of thousands of variants on activity and abundance

Understanding and predicting how amino acid substitutions affect proteins is key to our basic understanding of protein function and evolution. Amino acid changes may affect protein function in a number of ways including direct perturbations of activity or indirect effects on protein folding and stability. We have analysed 6749 experimentally determined variant effects from multiplexed assays on abundance and activity in two proteins (NUDT15 and PTEN) to quantify these effects, and find that a third of the variants cause loss of function, and about half of loss-of-function variants also have low cellular abundance. We analyse the structural and mechanistic origins of loss of function, and use the experimental data to find residues important for enzymatic activity. We performed computational analyses of protein stability and evolutionary conservation and show how we may predict positions where variants cause loss of activity or abundance. In this way, our results link thermodynamic stability and evolutionary conservation to experimental studies of different properties of protein fitness landscapes.

biophysics↗

Evolutionarily conserved chaperone-mediated proteasomal degradation of a disease-linked aspartoacylase variant

Canavan disease is a severe progressive neurodegenerative disorder that is characterized by swelling and spongy degeneration of brain white matter. The disease is genetically linked to polymorphisms in the aspartoacylase (ASPA) gene, including the substitution C152W. ASPA C152W is associated with greatly reduced protein levels in cells, yet biophysical experiments suggest a wild-type like thermal stability. Here, we examine the stability and degradation pathway of ASPA C152W. When we expressed ASPA C152W in Saccharomyces cerevisiae, we found a decreased steady state compared to wild-type ASPA as a result of increased proteasomal degradation. However, molecular dynamics simulations of ASPA C152W did not substantially deviate from wild-type ASPA, indicating that the native state is structurally preserved. Instead, we suggest that the C152W substitution prevents ASPA from reaching its stable native conformation, presumably by impacting on de novo folding. Systematic mapping of the protein quality control components acting on misfolded and aggregation-prone species of C152W, revealed that the degradation is highly dependent on the molecular chaperone Hsp70, its co-chaperone Hsp110 as well as several quality control E3 ubiquitin-protein ligases, including Ubr1. In human cells, ASPA C152W displayed increased proteasomal turnover that was similarly dependent on Hsp70 and Hsp110. We propose that Hsp110 is a potential therapeutic target for misfolding ASPA variants that trigger Canavan disease due to excessive degradation.

biochemistry↗

Zinc finger protein SALL4 functions through an AT-rich motif to regulate heterochromatin formation

SummaryThe zinc finger transcription factor SALL4 is highly expressed in embryonic stem cells, down-regulated in most adult tissues, but reactivated in many aggressive cancers. This unique expression pattern makes SALL4 an attractive target for designing therapeutic strategies. However, whether SALL4 binds DNA directly to regulate gene expression is unclear and many of its targets in cancer cells remain elusive. Here, through an unbiased screen of protein binding microarray (PBM) and Cleavage Under Targets and Release Using Nuclease (CUT&RUN) experiments, we identified and validated the DNA binding domain of SALL4 and its consensus binding sequence. Combined with RNA-seq analyses after SALL4 knockdown, we discovered hundreds of new SALL4 target genes that it directly regulates in aggressive liver cancer cells, including genes encoding a family of Histone 3 Lysine 9-specific Demethylases (KDMs). Taken together, these results elucidated the mechanism of SALL4 DNA binding and revealed novel pathways and molecules to target in SALL4-dependent tumors.Competing Interest StatementThe authors have declared no competing interest.View Full Text

molecular biology↗

Folliculin variants linked to Birt-Hogg-Dube syndrome are targeted for proteasomal degradation

Germline mutations in the folliculin (FLCN) tumor suppressor gene are linked to Birt-Hogg-Dube (BHD) syndrome, a dominantly inherited genetic disease characterized by predisposition to fibrofolliculomas, lung cysts, and renal cancer. Most BHD-linked FLCN variants include large deletions and splice site aberrations predicted to cause loss of function. The mechanisms by which missense variants and short in-frame deletions in FLCN trigger disease are unknown. Here, we present computational and experimental studies showing that the majority of such disease-causing FLCN variants cause loss of function due to proteasomal degradation of the encoded FLCN protein, rather than directly ablating FLCN function. Accordingly, several different single-site FLCN variants are present at strongly reduced levels in cells. In line with our finding that FLCN variants are protein quality control targets, several are also highly insoluble and fail to associate with the FLCN-binding partners FNIP1 and FNIP2. The lack of FLCN binding leads to rapid proteasomal degradation of FNIP1 and FNIP2. Half of the tested FLCN variants are mislocalized in cells, and one variant ({Delta}E510) forms perinuclear protein aggregates. A yeast-based screen revealed that the deubiquitylating enzyme Ubp15/USP7 and molecular chaperones regulate the turnover of the FLCN variants. Lowering the temperature to 29 {degrees}C led to a stabilization of two FLCN missense proteins, and for one variant (R362C), FLCN function was re-established at low temperature. In conclusion, we propose that most BHD-linked FLCN missense variants and small in-frame deletions operate by causing misfolding and degradation of the FLCN protein, and that stabilization of certain disease-linked variants may hold therapeutic potential.

molecular biology↗

Classifying disease-associated variants using measures of protein activity and stability

Decreased cost of human exome and genome sequencing provides new opportunities for diagnosing genetic disorders, but we need better and more robust methods for interpreting sequencing results including determining whether and by which mechanism a specific missense variants may be pathogenic. Using the protein PTEN (phosphatase and tensin homolog) as an example, we show how recent developments in both experiments and computational modelling can be used to determine whether a missense variant is likely to be pathogenic. One approach relies on multiplexed experiments that enable determination of the effect of all possible individual missense variants in a cellular assay. Another approach is to use computational methods to predict variant effects. We compare two different multiplexed experiments and two computational methods to classify variant effects in PTEN. We distinguish between methods that focus on effects on protein stability and protein-specific methods that are more directly related to enzyme activity. Our results on PTEN suggest that ~60% of pathogenic variants cause loss of function because they destabilise the folded protein which is subsequently degraded. Methods that quantify a broader range of effects on PTEN activity perform better at predicting variant effects. Either experimental method performs better than the corresponding computational predictions, so that e.g. experiments that probe cellular abundance perform better at identifying pathogenic variants than predictions of thermodynamic stability. Our results suggest that loss of stability of PTEN is a key driver for disease, and we hypothesize that experiments and prediction methods that probe protein stability can be used to find variants with similar mechanisms in other genes.

biophysics↗

Structural destabilization and chaperone-assisted proteasomal degradation of MLH1 as a mechanism for Lynch syndrome

Defective mismatch repair leads to increased mutation rates, and germline loss-of-function variants in the repair component MLH1 cause the hereditary cancer predisposition disorder known as Lynch syndrome. Early diagnosis is important, but complicated by many variants being of unknown significance. Here we show that a majority of the disease-linked MLH1 variants we studied are present at reduced cellular levels. We show that destabilized MLH1 variants are targeted for chaperone-assisted proteasomal degradation, resulting also in degradation of co-factors PMS1 and PMS2. In silico saturation mutagenesis and computational predictions of thermodynamic stability of MLH1 missense variants revealed a correlation between structural destabilization, reduced steady-state levels and loss-of-function. Thus, we suggest that loss of stability and cellular degradation is an important mechanism underlying many MLH1 variants in Lynch syndrome. Combined with analyses of conservation, the thermodynamic stability predictions separate disease-linked from benign MLH1 variants, and therefore hold potential for Lynch syndrome diagnostics.

biochemistry↗

Disharmony of the world’s island floras

Disharmony is a key concept in island biology that describes the biased representation of higher taxa on islands compared to their mainland source regions. Although differential colonization success of taxa is predicted by selective dispersal, environmental and biotic filtering, the empirical evidence for disharmony remains largely anecdotal. Here, we develop a novel method for delineating island source regions and present the first global quantitative assessment of island disharmony. We analyzed the overall compositional bias of 320 island floras and examined the over- or under-representation on islands for 450 plant families. We found that the compositional bias of island floras is strongly predicted by geographical and climatic island characteristics (isolation, area, geologic origin, temperature, precipitation), whereas the representation of individual families is only weakly related to family-specific characteristics (family size, family age, taxonomic group, functional traits), indicating that the taxonomic scope of the disharmony concept has historically limited its wider applicability. Our results provide a strong foundation for integrating disharmony with quantitative functional and phylogenetic approaches in order to gain a deeper understanding of assembly processes on islands.

ecology↗

Deep mutational scanning by FACS-sorting of encapsulated E. coli micro-colonies

We present a method for high-throughput screening of protein variants where the signal is enhanced by micro-encapsulation of single cells into 20-30 m agarose beads. Cells inside beads are propagated using standard agitation in liquid media and grow clonally into micro-colonies harboring several hundred bacteria. We have, as a proof-of-concept, analyzed random amino acid substitutions in the five C-terminal {beta}-strands of the Green Fluorescent Protein (GFP). Starting from libraries of variants, each bead represents a clonal line of cells that can be separated by Fluorescence Activated Cell Sorting (FACS). Pools representing collections of individual variants with desired properties are subsequently analyzed by deep sequencing. Notably, the encapsulation approach described holds the potential for high-throughput analysis of systems where the fluorescence signal from a single cell is insufficient for detection. Fusion to GFP, or use of fluorogenic substrates, allows coupling protein levels or activity to sequence for a wide range of proteins. Here we analyzed more than 10,000 individual variants to gauge the effect of mutations on GFP-fluorescence. In the mutated region, we observed virtually all amino acid substitutions that are accessible by single nucleotide exchange. Lastly, we assessed the performance of biophysical protein stability predictors, FoldX and Rosetta, in predicting the outcome of the experiment. Both tools display good performance on average, suggesting that loss of thermodynamic stability is a key mechanism for the observed variation of the mutants. This, in turn, suggests that deep mutational scanning datasets may be used to more efficiently fine-tune such predictors, especially for mutations poorly covered by current biophysical data.

bioengineering↗

Practical Unidentifiability Of Receptor Density In Target Mediated Drug Disposition Models Can Lead To Over-Interpretation Of Drug Concentration Data

For monoclonal antibodies, mathematical models of target mediated drug disposition (TMDD) are often fit to data in order to estimate key physiological parameters of the system. These parameter estimates can then be used to support drug development by assisting with the assessment of whether the target is druggable and what the first in human dose should be. The TMDD model is almost always over-parameterized given the available data, resulting in the practical unidentifiability of some of the model parameters, including the target receptor density. In particular, when only PK data is available, the receptor density is almost always practically unidentifiable. However, because practical identifiability is not regularly assessed, incorrect interpretation of model fits to the data can be made. This issue is illustrated using two case studies from the literature.

pharmacology and toxicology↗