Biology subjects

Fischer, S.

Publications and source records attributed to Fischer, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2021

Defining the extent of gene function using ROC curvature

Machine learning in genomics plays a key role in leveraging high-throughput data, but assessing the generalizability of performance has been a persistent challenge. Here, we propose to evaluate the generalizability of gene characterizations through the shape of performance curves. We identify Functional Equivalence Classes (FECs), uniform subsets of annotated and unannotated genes that jointly drive performance, by assessing the presence of straight lines in ROC curves. FECs are widespread across modalities and methods, and can be used to evaluate the extent and context-specificity of functional annotations in a data-driven manner. For example, FECs suggest that B cell markers can be decomposed into shared primary markers (10 to 50 genes), and tissue-specific secondary markers (100 to 500{square}genes). In addition, FECs are compatible with a wide range of functional encodings, with marker sets spanning at most 5% of the genome and data-driven extensions of Gene Ontology sets spanning up to 40% of the genome. Simple to assess visually and statistically, the identification of FECs in performance curves paves the way for novel functional characterization and increased robustness in analysis.

bioinformatics↗

bioRxiv2021

RNA interference mediates RNA toxicity with parent-of-origin effects in C. elegans expressing CTG repeats

Nucleotide repeat expansions are a hallmark of over 40 neurodegenerative diseases. These repeats cause RNA toxicity and trigger multisystemic symptoms that worsen with age. RNA toxicity can trigger, through an unclear mechanism, severe disease manifestation in infants that inherited repeats from their mothers. Here we show in Caenorhabditis elegans how RNA interference machinery causes intergenerational toxicity through inheritance of siRNAs derived from CUG repeats. The maternal repeat-derived small RNAs cause transcriptomic changes in the offspring, reduce motility and shorten lifespan. However, the toxicity phenotypes in the offspring can be rescued by perturbing the RNAi machinery in affected mothers. This points to a novel mechanism linking maternal bias and the RNAi machinery and suggests that toxic RNA is transmitted to offspring and causes disease phenotypes through intergenerational epigenetic inheritance.

molecular biology↗

bioRxiv2021

Meta-analytic markers reveal a generalizable description of cortical cell types

Our understanding of cell types has advanced considerably with the publication of single cell atlases. Marker genes play an essential role for experimental validation and computational analyses such as physiological characterization through pathway enrichment, annotation, and deconvolution. However, a framework for quantifying marker replicability and picking replicable markers is currently lacking. Here, using high quality data from the Brain Initiative Cell Census Network (BICCN), we systematically investigate marker replicability for 85 neuronal cell types. We show that, due to dataset-specific noise, we need to combine 5 datasets to obtain robust differentially expressed (DE) genes, particularly for rare populations and lowly expressed genes. We estimate that 10 to 200 meta-analytic markers provide optimal performance in downstream computational tasks. Replicable marker lists condense single cell atlases into interpretable and generalizable information about cell types, opening avenues for downstream applications, including cell type annotation, selection of gene panels and bulk data deconvolution.

bioinformatics↗

bioRxiv2021

Exploiting marker genes for robust classification and characterization of single-cell chromatin accessibility

MotivationSingle-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) is a valuable resource to learn cis-regulatory elements such as cell-type specific enhancers and transcription factor binding sites. However, cell-type identification of scATAC-seq data is known to be challenging due to the heterogeneity derived from different protocols and the high dropout rate. ResultsIn this study, we perform a systematic comparison of 7 scATAC-seq datasets of mouse brain to benchmark the efficacy of neuronal cell-type annotation from gene sets. We find that redundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation across the data collected from different studies. Interestingly, simple aggregation of such marker genes achieves performance comparable or higher than that of machine-learning classifiers, suggesting its potential for downstream applications. Based on our results, we reannotated all scATAC-seq data for detailed cell types using robust marker genes. Their meta scATAC-seq profiles are publicly available at https://gillisweb.cshl.edu/Meta_scATAC. Furthermore, we trained a deep neural network to predict chromatin accessibility from only DNA sequence and identified key motifs enriched for each neuronal subtype. Those predicted profiles are visualized together in our database as a valuable resource to explore cell-type specific epigenetic regulation in a sequence-dependent and -independent manner. Contactjesse.gillis@utoronto.ca Supplementary informationSupplementary data are available at xxxxxx online. Key pointsO_LI7 scATAC-seq datasets of mouse brain are systematically compared to benchmark the efficacy of neuronal cell-type annotation from gene sets. C_LIO_LIRedundant marker genes give a dramatic improvement for a sparse scATAC-seq annotation beyond the heterogeneity of scATAC-seq data. C_LIO_LIWe reannotated all scATAC-seq data for detailed cell types using robust marker genes and their meta scATAC-seq profiles are publicly available at a new Meta scATAC-seq server. C_LIO_LIPredicted profiles from only DNA sequence using a deep neural network are visualized together to explore sequence-dependent and -independent epigenetic regulation. C_LI

bioinformatics↗

bioRxiv2021

Single Cell, Single Nucleus and Spatial RNA Sequencing of the Human Liver Identifies Hepatic Stellate Cell and Cholangiocyte Heterogeneity

The critical functions of the human liver are coordinated through the interactions of hepatic parenchymal and non-parenchymal cells. Recent advances in single cell transcriptional approaches have enabled an examination of the human liver with unprecedented resolution. However, dissociation related cell perturbation can limit the ability to fully capture the human livers parenchymal cell fraction, which limits the ability to comprehensively profile this organ. Here, we report the transcriptional landscape of 73,295 cells from the human liver using matched single-cell RNA sequencing (scRNA-seq) and single-nucleus RNA sequencing (snRNA-seq). The addition of snRNA-seq enabled the characterization of interzonal hepatocytes at single-cell resolution, revealed the presence of rare subtypes of hepatic stellate cells previously only seen in disease, and detection of cholangiocyte progenitors that had only been observed during in vitro differentiation experiments. However, T and B lymphocytes and NK cells were only distinguishable using scRNA-seq, highlighting the importance of applying both technologies to obtain a complete map of tissue-resident cell-types. We validated the distinct spatial distribution of the hepatocyte, cholangiocyte and stellate cell populations by an independent spatial transcriptomics dataset and immunohistochemistry. Our study provides a systematic comparison of the transcriptomes captured by scRNA-seq and snRNA-seq and delivers a high-resolution map of the parenchymal cell populations in the healthy human liver.

cell biology↗

bioRxiv2020

A precautionary solution to estimation bias in shaping safe harvest boundaries

Biased estimates of population status are a pervasive conservation problem. This problem has plagued assessments of commercial exploitation of marine species and can threaten the sustainability of both populations and fisheries. We develop a computer-intensive approach to minimize adverse effects of persistent estimation bias in assessments by optimizing operational harvest measures (harvest control rules) with closed-loop simulation of resource-management feedback systems: management strategy evaluation. Using saithe (Pollachius virens), a bottom-water, apex predator in the North Sea, as a real-world case study, we illustrate the approach by first diagnosing robustness of the existing harvest control rule and then optimizing it through propagation of biases (overestimated stock abundance and underestimated fishing pressure) along with select process and observation uncertainties. Analyses showed that severe biases lead to overly optimistic catch limits and then progressively magnify the amplitude of catch fluctuation, thereby posing unacceptably high overharvest risks. Consistent performance of management strategies to conserve the resource can be achieved by developing more robust control rules. These rules explicitly account for estimation bias through a computational grid search for a set of control parameters (threshold abundance that triggers management action, Btrigger, and target exploitation rate, Ftarget) that maximize yield while keeping stock abundance above a precautionary level. When the biases become too severe, optimized control parameters- for saithe, raising Btrigger and lowering Ftarget-would safeguard against overharvest risk (<3.5% probability of stock depletion) and provide short-term stability in catch limit (<20% year-to-year variation), thereby minimizing disruption to fishing communities. The precautionary approach to fine-tuning adaptive risk management through management strategy evaluation offers a powerful tool to better shape sustainable harvest boundaries for exploited resource populations when estimation bias persists. By explicitly accounting for emergent sources of uncertainty our proposed approach ensures effective conservation and sustainable exploitation of living marine resources even under profound uncertainty. Open Research StatementData sets and code utilized for this research are available on Figshare. DOI: https://doi.org/10.6084/m9.figshare.13281266

ecology↗

bioRxiv2020

Replicability of spatial gene expression atlas data from the adult mouse brain

BackgroundSpatial gene expression is particularly interesting in the mammalian brain, with the potential to serve as a link between many data types. However, as with any type of expression data, cross-dataset benchmarking of spatial data is a crucial first step. Here, we assess the replicability, with reference to canonical brain sub-divisions, between the Allen Institutes in situ hybridization data from the adult mouse brain (ABA) and a similar dataset collected using Spatial Transcriptomics (ST). With the advent of tractable spatial techniques, for the first time we are able to benchmark the Allen Institutes whole-brain, whole-transcriptome spatial expression dataset with a second independent dataset that similarly spans the whole brain and transcriptome. ResultsWe use LASSO, linear regression, and correlation-based feature selection in a supervised learning framework to classify expression samples relative to their assayed location. We show that Allen reference atlas labels are classifiable using transcription, but that performance is higher in the ABA than ST. Further, models trained in one dataset and tested in the opposite dataset do not reproduce classification performance bi-directionally. Finally, while an identifying expression profile can be found for a given brain area, it does not generalize to the opposite dataset. ConclusionsIn general, we found that canonical brain area labels are classifiable in gene expression space within dataset and that our observed performance is not merely reflecting physical distance in the brain. However, we also show that cross-platform classification is not robust. Emerging spatial datasets from the mouse brain will allow further characterization of cross-dataset replicability.

genomics↗

bioRxiv2020

Cellular Anatomy of the Mouse Primary Motor Cortex

An essential step toward understanding brain function is to establish a cellular-resolution structural framework upon which multi-scale and multi-modal information spanning molecules, cells, circuits and systems can be integrated and interpreted. Here, through a collaborative effort from the Brain Initiative Cell Census Network (BICCN), we derive a comprehensive cell type-based description of one brain structure - the primary motor cortex upper limb area (MOp-ul) of the mouse. Applying state-of-the-art labeling, imaging, computational, and neuroinformatics tools, we delineated the MOp-ul within the Mouse Brain 3D Common Coordinate Framework (CCF). We defined over two dozen MOp-ul projection neuron (PN) types by their anterograde targets; the spatial distribution of their somata defines 11 cortical sublayers, a significant refinement of the classic notion of cortical laminar organization. We further combine multiple complementary tracing methods (classic tract tracing, cell type-based anterograde, retrograde, and transsynaptic viral tracing, high-throughput BARseq, and complete single cell reconstruction) to systematically chart cell type-based MOp input-output streams. As PNs link distant brain regions at synapses as well as host cellular gene expression, our construction of a PN type resolution MOp-ul wiring diagram will facilitate an integrated analysis of motor control circuitry across the molecular, cellular, and systems levels. This work further provides a roadmap towards a cellular resolution description of mammalian brain architecture.

neuroscience↗

bioRxiv2020

Integrating barcoded neuroanatomy with spatial transcriptional profiling reveals cadherin correlates of projections shared across the cortex

Functional circuits consist of neurons with diverse axonal projections and gene expression. Understanding the molecular signature of projections requires high-throughput interrogation of both gene expression and projections to multiple targets in the same cells at cellular resolution, which is difficult to achieve using current technology. Here, we introduce BARseq2, a technique that simultaneously maps projections and detects multiplexed gene expression by in situ sequencing. We determined the expression of cadherins and cell-type markers in 29,933 cells, and the projections of 3,164 cells in both the mouse motor cortex and auditory cortex. Associating gene expression and projections in 1,349 neurons revealed shared cadherin signatures of homologous projections across the two cortical areas. These cadherins were enriched across multiple branches of the transcriptomic taxonomy. By correlating multi-gene expression and projections to many targets in single neurons with high throughput, BARseq2 provides a path to uncovering the molecular logic underlying neuronal circuits.

neuroscience↗

bioRxiv2020

Evolution of cellular diversity in primary motor cortex of human, marmoset monkey, and mouse

The primary motor cortex (M1) is essential for voluntary fine motor control and is functionally conserved across mammals. Using high-throughput transcriptomic and epigenomic profiling of over 450,000 single nuclei in human, marmoset monkey, and mouse, we demonstrate a broadly conserved cellular makeup of this region, whose similarity mirrors evolutionary distance and is consistent between the transcriptome and epigenome. The core conserved molecular identity of neuronal and non-neuronal types allowed the generation of a cross-species consensus cell type classification and inference of conserved cell type properties across species. Despite overall conservation, many species specializations were apparent, including differences in cell type proportions, gene expression, DNA methylation, and chromatin state. Few cell type marker genes were conserved across species, providing a short list of candidate genes and regulatory mechanisms responsible for conserved features of homologous cell types, such as the GABAergic chandelier cells. This consensus transcriptomic classification allowed the Patch-seq identification of layer 5 (L5) corticospinal Betz cells in non-human primate and human and characterization of their highly specialized physiology and anatomy. These findings highlight the robust molecular underpinnings of cell type diversity in M1 across mammals and point to the genes and regulatory pathways responsible for the functional identity of cell types and their species-specific adaptations.

neuroscience↗

bioRxiv2020

Convergence and novelty in adaptation to whole genome duplication in three independent polyploids

Convergent evolution is observed broadly across the web of life, but the degree of evolutionary constraint during adaptation of core intracellular processes is not known. High constraint has been assumed for conserved processes, such as cell division and DNA repair, but reports of nimble evolutionary shifts in these processes have confounded this expectation. Whole genome duplication (WGD) necessitates the concerted adjustment of a wide range of fundamental intracellular functions but nevertheless has been repeatedly survived in all kingdoms. Given this repeated adaptation to WGD despite obvious intracellular challenges to core processes such as meiosis, we asked: how do lineages not only survive WGD, but sometimes ultimately thrive? Are the solutions employed constrained or diverse? Here we detect genes and processes under selection following WGD in the Cochlearia species complex by performing a scan for selective sweeps following WGD in a large-scale survey of 73 resequenced individuals from 23 populations across Europe. We then contrast our results from two independent WGDs in Arabidopsis arenosa and Cardamine amara. We find that while WGD does require the adaptation of particular functional processes in all three cases, the specific genes recruited to respond are highly flexible. We also observe evidence of varying degrees of convergence between different cases. Our results point to a polygenic basis for the distributed adaptive systems that control meiotic crossover number, ionomic rewiring, cell cycle control, and nuclear regulation. Given the sheer number of loci under selection post-WGD, we surmise that this polygenicity may explain the general lack of convergence between these species that are ~30 million years diverged. Based on our results, we speculate that adaptive processes themselves - such as the rate of generation of structural genomic variants--may be altered by WGD in nascent autopolyploids, contributing to the occasionally spectacular adaptability of autopolyploids observed across kingdoms.

evolutionary biology↗

bioRxiv2020

Light-driven formation of high-valent manganese oxide by photosystem II supports evolutionary role in early bioenergetics

Water oxidation and concomitant O2-formation by the Mn4Ca cluster of oxygenic photosynthesis has shaped the biosphere, atmosphere, and geosphere. It has been hypothesized that at an early stage of evolution, before photosynthetic water oxidation became prominent, photosynthetic formation of Mn oxides from dissolved Mn(2+) ions may have played a key role in bioenergetics and possibly facilitated early geological manganese deposits. The biochemical evidence for the ability of photosystems to form extended Mn oxide particles, lacking until now, is provided herein. We tracked the light-driven redox processes in spinach photosystem II (PSII) particles devoid of the Mn4Ca clusters by UV-vis and X-ray spectroscopy. We find that oxidation of aqueous Mn(2+) ions results in PSII-bound Mn(III,IV)-oxide nanoparticles of the birnessite type comprising 50-100 Mn ions per PSII. Having shown that even todays photosystem-II can form birnessite-type oxide particles efficiently, we propose an evolutionary scenario, which involves Mn-oxide production by ancestral photosystems, later followed by down-sizing of protein-bound Mn-oxide nanoparticles to finally yield todays Mn4CaO5 cluster of photosynthetic water oxidation.

biophysics↗

bioRxiv2020

Improving replicability in single-cell RNA-Seq cell type discovery with Dune

Single-cell transcriptome sequencing (scRNA-Seq) has allowed many new types of investigations at unprecedented and unique levels of resolution. Among the primary goals of scRNA-Seq is the classification of cells into potentially novel cell types. Many approaches build on the existing clustering literature to develop tools specific to single-cell applications. However, almost all of these methods rely on heuristics or user-supplied parameters to control the number of clusters identified. This affects both the resolution of the clusters within the original dataset as well as their replicability across datasets. While many recommendations exist to select these tuning parameters, most of them are quite ad hoc. In general, there is little assurance that any given set of parameters will represent an optimal choice in the ever-present trade-off between cluster resolution and replicability. For instance, it may be the case that another set of parameters will result in more clusters that are also more replicable, or in fewer clusters that are also less replicable. Here, we propose a new method called Dune for optimizing the trade-off between the resolution of the clusters and their replicability across datasets. Our method takes as input a set of clustering results on a single dataset, derived from any set of clustering algorithms and associated tuning parameters, and iteratively merges clusters within partitions in order to maximize their concordance between partitions. As demonstrated on a variety of scRNA-Seq datasets from different platforms, Dune outperforms existing techniques, that rely on hierarchical merging for reducing the number of clusters, in terms of replicability of the resultant merged clusters. It provides an objective approach for identifying replicable consensus clusters most likely to represent common biological features across multiple datasets.

bioinformatics↗

bioRxiv2020

An integrated transcriptomic and epigenomic atlas of mouse primary motor cortex cell types

Single cell transcriptomics has transformed the characterization of brain cell identity by providing quantitative molecular signatures for large, unbiased samples of brain cell populations. With the proliferation of taxonomies based on individual datasets, a major challenge is to integrate and validate results toward defining biologically meaningful cell types. We used a battery of single-cell transcriptome and epigenome measurements generated by the BRAIN Initiative Cell Census Network (BICCN) to comprehensively assess the molecular signatures of cell types in the mouse primary motor cortex (MOp). We further developed computational and statistical methods to integrate these multimodal data and quantitatively validate the reproducibility of the cell types. The reference atlas, based on more than 600,000 high quality single-cell or -nucleus samples assayed by six molecular modalities, is a comprehensive molecular account of the diverse neuronal and non-neuronal cell types in MOp. Collectively, our study indicates that the mouse primary motor cortex contains over 55 neuronal cell types that are highly replicable across analysis methods, sequencing technologies, and modalities. We find many concordant multimodal markers for each cell type, as well as thousands of genes and gene regulatory elements with discrepant transcriptomic and epigenomic signatures. These data highlight the complex molecular regulation of brain cell types and will directly enable design of reagents to target specific MOp cell types for functional analysis.

neuroscience↗

bioRxiv2020

Alzheimer's disease-relevant tau modifications selectively impact neurodegeneration and mitophagy in a novel C. elegans single-copy transgenic model

BackgroundA defining pathological hallmark of the progressive neurodegenerative disorder Alzheimers disease (AD) is the accumulation of misfolded tau with abnormal post-translational modifications (PTMs). These include phosphorylation at Threonine 231 (T231) and acetylation at Lysine 274 (K274) and at Lysine 281 (K281). Although tau is recognized to play a central role in pathogenesis of AD, the precise mechanisms by which these abnormal PTMs contribute to the neural toxicity of tau is unclear. MethodsHuman 0N4R tau (wild type) was expressed in touch receptor neurons of the genetic model organism C. elegans through single-copy gene insertion. Defined mutations were then introduced into the single-copy tau transgene through CRISPR-Cas9 genome editing. These mutations included T231E and T231A, to mimic phosphorylation and phospho-ablation of a commonly observed pathological epitope, respectively, and K274/281Q, to mimic disease-associated lysine acetylation. Stereotypical touch response assays were used to assess behavioral defects in the transgenic strains as a function of age, and genetically-encoded fluorescent biosensors were used to measure the morphological dynamics and turnover of touch neuron mitochondria. ResultsUnlike existing tau overexpression models, C. elegans single-copy expression of tau did not elicit overt pathological phenotypes at baseline. However, strains expressing disease associated PTM-mimetics (T231E and K274/281Q) exhibited reduced touch sensation and morphological abnormalities that increased with age. In addition, the PTM-mimetic mutants lacked the ability to engage mitophagy in response to mitochondrial stress. ConclusionsLimiting the expression of tau results in a genetic model where pathological modifications and age result in evolving phenotypes, which may more closely resemble the normal progression of AD. The finding that disease-associated PTMs suppress compensatory responses to mitochondrial stress provides a new perspective into the pathogenic mechanisms underlying AD.

neuroscience↗

bioRxiv2019

Caenorhabditis elegans ADAR editing and the ERI-6/7/MOV10 RNAi pathway silence endogenous viral elements and LTR retrotransposons

Endogenous retroviruses and LTR retrotransposons are mobile genetic elements that are closely related to retroviruses. Desilenced endogenous retroviruses are associated with human autoimmune disorders and neurodegenerative diseases. C. elegans and related Caenorhabdites contain LTR retrotransposons and, as described here, numerous integrated viral genes including viral envelope genes that are part of LTR retrotransposons. We found that both LTR retrotransposons and endogenous viral elements are silenced by ADARs (adenosine deaminases acting on double-stranded RNA (dsRNA)) together with the endogenous RNAi factor ERI-6/7, a homolog of Mov10 helicase, a retrotransposon and retrovirus restriction factor in human. siRNAs corresponding to integrated viral genes and LTR retrotransposons, but not to DNA transposons, are dependent on the ADARs and ERI-6/7; on the contrary, siRNAs corresponding to palindromic repeats are increased in adar-eri mutants because of an antiviral RNAi response to dsRNA. Silencing of LTR retrotransposons is dependent on downstream RNAi factors and P granule components but is independent of the viral sensor DRH-1/RIG-I and the nuclear Argonaute NRDE-3. The activation of retrotransposons in the ADAR- and ERI-6/7/MOV10-defective mutant is associated with the induction of the Unfolded Protein Response (UPR), a common response to viral infection. The overlap between genes induced upon viral infection and infection with intracellular pathogens, and genes co-expressed with retrotransposons, suggests that there is a common response to different types of foreign elements that includes a response to proteotoxicity presumably caused by the burden of replicating pathogens and expressed retrotransposons.\n\nSIGNIFICANCESilencing of transposable elements and viruses is critical for the maintenance of genome integrity, cellular homeostasis and organismal health. Here we describe multiple factors that control different types of transposable elements, providing insight into how they are regulated. We also identify stress response pathways that are triggered upon mis-regulation of these transposable elements. The conservation of these factors and pathways in human suggests that our studies in C. elegans can provide general insight into the regulation of and response to transposable elements and viruses.

genetics↗

bioRxiv2018

The Drosophila fussel gene is required for bitter gustatory neuron differentiation acting within an Rpd3 dependent chromatin modifying complex

Members of the Ski/Sno protein family are classified as proto-oncogenes and act as negative regulators of the TGF-{beta}/BMP-pathways in vertebrates and invertebrates. A newly identified member of this protein family is fussel (fuss), the Drosophila homologue of the human functional Smad suppressing elements (fussel-15 and fussel-18). We and others have shown that Fuss interacts with SMAD4 and that overexpression leads to a strong inhibition of Dpp signaling. However, to be able to characterize the endogenous Fuss function in Drosophila melanogaster, we have generated a number of state of the art tools including anti-Fuss antibodies, specific fuss-Gal4 lines and fuss mutant fly lines via the CRISPR/Cas9 system. Fuss is a predominantly nuclear, postmitotic protein, mainly expressed in interneurons and fuss mutants are fully viable without any obvious developmental phenotype. To identify potential target genes or cells affected in fuss mutants, we conducted targeted DamID experiments in adult flies, which revealed the function of fuss in bitter gustatory neurons. We fully characterized fuss expression in the adult proboscis and by using food choice assays we were able to show that fuss mutants display defects in detecting bitter compounds. This correlated with a reduction of gustatory receptor gene expression (Gr33a, Gr66a, Gr93a) providing a molecular link to the behavioral phenotype. In addition, Fuss interacts with Rpd3, and downregulation of rpd3 in gustatory neurons phenocopies the loss of Fuss expression. Surprisingly, there is no colocalization of Fuss with phosphorylated Mad in the larval central nervous system, excluding a direct involvement of Fuss in Dpp/BMP signaling.\n\nHere we provide a first and exciting link of Fuss function in gustatory bitter neurons. Although gustatory receptors have been well characterized, little is known regarding the differentiation and maturation of gustatory neurons. This work therefore reveals Fuss as a pivotal element for the proper differentiation of bitter gustatory neurons acting within a chromatin modifying complex.

developmental biology↗

bioRxiv2018

The molecular recognition of phosphatidic acid by an amphipathic helix in Opi1

A key event in cellular physiology is the decision between membrane biogenesis and fat storage. Phosphatidic acid (PA) is an important lipid intermediate and signaling lipid at the branch point of these pathways and constantly monitored by the transcriptional repressor Opi1 to orchestrate lipid metabolism. Here, we report on the mechanism of membrane recognition by Opi1 and identify an amphipathic helix (AH) for the selective binding to membranes containing PA over phosphatidylserine (PS). The insertion of the AH into the hydrophobic core of the membrane renders Opi1 sensitive to the lipid acyl chain composition as an important factor contributing to the regulation of membrane biogenesis. Based on these findings, we rationally designed the membrane binding properties of Opi1 to control its responsiveness in the physiological context. Using extensive molecular dynamics (MD) simulations, we identified two PA-selective three-finger grips that tightly bind the phosphate headgroup, while interacting less intimately and more transiently with PS. This work establishes lipid headgroup selectivity as a new feature in the family of AH-containing membrane property sensors.

biochemistry↗