Biology subjects

Pechmann, S.

Publications and source records attributed to Pechmann, S..

8 recordsLinked to original sources

bioRxiv2024

Heterogeneous folding landscapes and predetermined breaking points within a protein family

The accurate prediction of protein structures with artificial intelligence has been a spectacular success. Yet, how proteins fold into their native structures inside the cell remains incompletely understood. Of particular interest is to rationalize how proteins interact with the protein homeostasis network, an organism specific set of protein folding and quality control enzymes. Failure of protein homeostasis leads to widespread misfolding and aggregation, and thus neurodegeneration. Here, I present a comparative analysis of the folding across a protein family from a single organism, the Saccharomyces cerevisiae small GTPases. Using computational modelling to directly probe folding dynamics, this work shows how near identical structures from the same folding environment exhibit heterogeneous folding landscapes. Remarkably, yeast small GTPases are found to unfold along different pathways either via the N- or C-terminus initiated by structure-encoded predetermined breaking points. Moreover, degrons as recognition signals for ubiquitin-dependent degradation were systematically depleted from the initial unfolding sites, as if to protect from too rapid degradation upon spontaneous unfolding. In turn, Hsp70 Ssb chaperone binding correlated only with N-terminal hydrophobicity. The presented results highlight a direct coordination of folding pathway and protein homeostasis interaction signals across a protein family. A deeper understanding of the interdependence of proteins with their folding environment will help to rationalize and combat disease linked to protein misfolding and dysregulation. More generally, this work underlines the importance of understanding protein folding in the cellular context, and highlights valuable constraints towards a systems-level understanding of protein homeostasis.

bioinformatics↗

bioRxiv2023

Single-cell expression predicts neuron specific proteinhomeostasis networks

The protein homeostasis network keeps proteins in their correct shapes and avoids unwanted protein aggregation. In turn, the accumulation of aberrantly misfolded proteins has been directly associated with the onset of aging-associated neurodegenerative diseases such as Alzheimers and Parkinsons. However, a detailed and rational understanding of how protein homeostasis is achieved in health, and how it can be targeted for therapeutic intervention in diseases remains missing. Here, large-scale single-cell expression data from the Allen Brain Map is analyzed to investigate the transcription regulation of the core protein homeostasis network across the human brain. Remarkably, distinct expression profiles suggest specialized protein homeostasis networks with systematic adaptations in excitatory neurons, inhibitory neurons, and non-neuronal cells. Moreover, several chaperones and Ubiquitin ligases are found transcriptionally coregulated with genes important for synapse formation and maintenance, thus linking protein homeostasis to the regulation of neuronal function. Finally, evolutionary analyses highlight the conservation of an elevated interaction density in the chaperone network, suggesting that one of the most exciting aspects of chaperone action may yet be discovered in their collective action at the systems level. More generally, our work highlights the power of computational analyses for breaking down complexity and gaining complementary insights into fundamental biological problems.

genomics↗

bioRxiv2021

Functional network motifs defined through integrationof protein-protein and genetic interactions

Cells are enticingly complex systems. The identification of feedback regulation is critically important for understanding this complexity. Network motifs defined as small graphlets that occur more frequently than expected by chance have revolutionized our understanding of feed-back circuits in cellular networks. However, with their definition solely based on statistical over-representation, network motifs often lack biological context, which limits their usefulness. Here, we define functional network motifs (FNMs) through the systematic integration of genetic interaction data that directly informs on functional relationships between genes and encoded proteins. Occurring two orders of magnitude less frequently than conventional network motifs, we found FNMs significantly enriched in genes known to be functionally related. Moreover, our comprehensive analyses of FNMs in yeast showed that they are powerful at capturing both known and putative novel regulatory interactions, thus suggesting a promising strategy towards the systematic identification of feedback regulation in biological networks. Many FNMs appeared as excellent candidates for the prioritization of follow-up biochemical characterization, which is a recurring bottleneck in the targeting of complex diseases. More generally, our work highlights a fruitful avenue for integrating and harnessing genomic network data.

bioinformatics↗

bioRxiv2020

Programmed trade-offs in protein folding networks

Maintaining protein homeostasis, i.e. a folded and functional proteome, depends on the efficient allocation of cellular protein quality control resources. Decline and dysregulation of protein homeostasis are directly associated to conditions of aging and neurodegeneration. Molecular chaperones as specialized protein quality control enzymes form the core of protein homeostasis. However, how chaperones selectively interact with their substrate proteins thus allocate their overall limited capacity remains poorly understood. Here, I present an integrated analysis of sequence and structural determinants that define interactions of the Saccharomyces cerevisiae Hsp70 Ssb. Structural homologues that differentially interact with Ssb for de novo folding were found to systematically differ in complexity of their folding landscapes, selective use of nonoptimal codons, and presence of short discriminative sequences. All analyzed characteristics contributed to the prediction of Ssb interactions in highly complementary manner, highlighting pervasive trade-offs in chaperone-assisted protein folding landscapes. However, short discriminative sequences were found to contribute by far the strongest signal towards explaining Ssb interactions. This observation suggested that some chaperone interactions may be directly programmed in the amino acid sequences rather than responding to folding challenges, possibly for regulatory advantages.

bioinformatics↗

bioRxiv2019

Inferring translational heterogeneity from ribosome profiling data

Translation of messenger RNAs into proteins by the ribosome is the most important step of protein biosynthesis. Accordingly, translation is tightly controlled and heavily regulated to maintain cellular homeostasis. Ribosome profiling (Ribo-seq) has revolutionized the study of translation by revealing many of its underlying mechanisms. However, equally many aspects of translation remain mysterious, in part also due to persisting challenges in the interpretation of data obtained from Ribo-seq experiments. Here, we show that some of the variability observed in Ribo-seq data has biological origins and reflects programmed heterogeneity of translation. To systematically identify sequences that are differentially translated (DT) across mRNAs beyond what can be attributed to experimental variability, we performed a comparative analysis of Ribo-seq data from Saccharomyces cerevisiae and derived a consensus ribosome density profile that reflects consistent signals in individual experiments. Remarkably, the thus identified DT sequences link to mechanisms known to regulate translation elongation and are enriched in genes important for protein and organelle biosynthesis. Our results thus highlight examples of translational heterogeneity that are encoded in the genomic sequences and tuned to optimizing cellular homeostasis. More generally, our work highlights the power of Ribo-seq to understand the complexities of translation regulation.

bioinformatics↗

bioRxiv2019

Pervasive convergent evolution and extreme phenotypes define chaperone requirements of protein homeostasis

Maintaining protein homeostasis is an essential requirement for cell and organismal viability. An elaborate regulatory system within cells, the protein homeostasis network, safeguards that proteins are correctly folded and functional. At the heart of this regulatory system lies a class of specialized protein quality control enzymes called chaperones that are tasked with assisting proteins in their folding, avoiding aggregation, and degradation. Failure and decline of protein homeostasis are directly associated with conditions of aging and aging-related neurodegenerative diseases such as Alzheimers and Parkinsons. However, it is not clear what tips the balance of protein homeostasis and leads to onset of aging and diseases. Here, we present a comparative genomics analysis of protein homeostasis in eukaryotes and report general principles of maintaining protein homeostasis across the eukaryotic tree of life. Expanding a previous analysis of 16 eukaryotes to 216 eukaryotic genomes, we find a strong correlation between the size of eukaryotic chaperone networks and size of the genomes that is distinct for different species kingdoms. Importantly, organisms with pronounced phenotypes clearly buck this trend. Northobranchius furzeri, the shortest-lived vertebrate and widely used model for fragile protein homeostasis is found to be chaperone limited. Heterocephalus glaber as the longest-lived rodent thus especially robust organism is characterized by above average numbers of chaperones. Our work thus indicates that the balance in protein homeostasis may be a key variable in explaining organismal robustness. Finally, our work provides an elegant example of harnessing the power of evolution and comparative genomics to address fundamental open questions in biology with direct relevance to human diseases.

evolutionary biology↗

bioRxiv2018

Improvement of the memory function by negative autoregulation of a mutual repression network in a stochastic environment

BackgroundCellular memory is a ubiquitous function of biological systems. By generating a sustained response to a transient inductive stimulus, often due to bistability, memory is central to the robust control of many important biological processes. However, our understanding of the origins of cellular memory remains incomplete. Stochastic fluctuations that are inherent to most biological systems have been shown to hamper memory function. Yet, how stochasticity changes the behavior of genetic circuits is generally not clear from a deterministic analysis of the network alone. Here, we apply deterministic rate equations, stochastic simulations, and theoretical analyses of Fokker-Planck equations to investigate how intrinsic noise affects the memory function in a mutual repression network.\n\nResultsWe find that the addition of negative autoregulation improves the persistence of memory in a small gene regulatory network by reducing stochastic fluctuations. Our theoretical analyses reveal that this improved memory function stems from an increased stability of the steady states of the system. Moreover, we show how the tuning of critical network parameters can further enhance memory.\n\nConclusionsOur work illuminates the power of stochastic and theoretical approaches to understanding biological circuits, and the importance of considering stochasticity to designing synthetic circuits with memory function.

systems biology↗

bioRxiv2017

Hsp90 dictates viral sequence space by balancing the evolutionary tradeoffs between protein stability, aggregation and translation rate

Acquisition of mutations is central to evolution but the detrimental effects of most mutations on protein folding and stability limit protein evolvability. Molecular chaperones, which suppress aggregation and facilitate polypeptide folding, are proposed to promote sequence diversification by buffering destabilizing mutations. However, whether and how chaperones directly control protein evolution remains poorly understood. Here, we examine the effect of reducing the activity of the key eukaryotic chaperone Hsp90 on poliovirus evolution. Contrary to predictions of a buffering model, inhibiting Hsp90 increases population sequence diversity and promotes accumulation of mutations reducing protein stability. Explaining this counterintuitive observation, we find that Hsp90 offsets the evolutionary tradeoff between protein stability and aggregation. Lower chaperone levels favor sequence variants of reduced hydrophobicity, thus decreasing protein aggregation propensity but at a cost to protein stability. Notably, reducing Hsp90 activity also promotes clusters of codon-deoptimized synonymous mutations at inter-domain boundaries, likely to promote local ribosomal slowdown to facilitate cotranslational domain folding. Our results reveal how a chaperone can shape the sequence landscape at both the protein and RNA levels to harmonize the competing constraints posed by protein stability, aggregation propensity and translation rate on successful protein biogenesis.

evolutionary biology↗