Biology subjects

Klein, M.

Publications and source records attributed to Klein, M..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Mapping cells through time and space with moscot

Single-cell genomics technologies enable multimodal profiling of millions of cells across temporal and spatial dimensions. Experimental limitations prevent the measurement of all-encompassing cellular states in their native temporal dynamics or spatial tissue niche. Optimal transport theory has emerged as a powerful tool to overcome such constraints, enabling the recovery of the original cellular context. However, most algorithmic implementations currently available have not kept up the pace with increasing dataset complexity, so that current methods are unable to incorporate multimodal information or scale to single-cell atlases. Here, we introduce multi-omics single-cell optimal transport (moscot), a general and scalable framework for optimal transport applications in single-cell genomics, supporting multimodality across all applications. We demonstrate moscots ability to efficiently reconstruct developmental trajectories of 1.7 million cells of mouse embryos across 20 time points and identify driver genes for first heart field formation. The moscot formulation can be used to transport cells across spatial dimensions as well: To demonstrate this, we enrich spatial transcriptomics datasets by mapping multimodal information from single-cell profiles in a mouse liver sample, and align multiple coronal sections of the mouse brain. We then present moscot.spatiotemporal, a new approach that leverages gene expression across spatial and temporal dimensions to uncover the spatiotemporal dynamics of mouse embryogenesis. Finally, we disentangle lineage relationships in a novel murine, time-resolved pancreas development dataset using paired measurements of gene expression and chromatin accessibility, finding evidence for a shared ancestry between delta and epsilon cells. Moscot is available as an easy-to-use, open-source python package with extensive documentation at https://moscot-tools.org.

bioinformatics↗

bioRxiv2023

Mapping lineage-traced cells across time points with moslin

Simultaneous profiling of single-cell gene expression and lineage history holds enormous potential for studying cellular decision-making beyond simpler pseudotime-based approaches. However, it is currently unclear how lineage and gene expression information across experimental time points can be combined in destructive experiments, which is particularly challenging for in-vivo systems. Here we present moslin, a Fused Gromov-Wasserstein-based model to couple matching cellular profiles across time points. In contrast to existing methods, moslin leverages both intra-individual lineage relations and inter-individual gene expression similarity. We demonstrate on simulated and real data that moslin outperforms state-of-the-art approaches that use either one or both data modalities, even when the lineage information is noisy. On C. elegans embryonic development, we show how moslin, combined with trajectory inference methods, predicts fate probabilities and putative decision driver genes. Finally, we use moslin to delineate lineage relationships among transiently activated fibroblast states during zebrafish heart regeneration. We anticipate moslin to play a crucial role in deciphering complex state change trajectories from lineage-traced single-cell data.

bioinformatics↗

bioRxiv2023

Continuous, long-term crawling behavior characterized by a robotic transport system

Detailed descriptions of behavior provide critical insight into the structure and function of nervous systems. In Drosophila larvae and many other systems, short behavioral experiments have been successful in characterizing rapid responses to a range of stimuli at the population level. However, the lack of long-term continuous observation makes it difficult to dissect comprehensive behavioral dynamics of individual animals and how behavior (and therefore the nervous system) develops over time. To allow for long-term continuous observations in individual fly larvae, we have engineered a robotic instrument that automatically tracks and transports larvae throughout an arena. The flexibility and reliability of its design enables controlled stimulus delivery and continuous measurement over developmental time scales, yielding an unprecedented level of detailed locomotion data. We utilize the new systems capabilities to perform continuous observation of exploratory behavior over a duration of six hours with and without a thermal gradient present, and in a single larva for over 30 hours. Long-term free-roaming behavior and analogous short-term experiments show similar dynamics that take place at the beginning of each experiment. Finally, characterization of larval thermotaxis in individuals reveals a bimodal distribution in navigation efficiency, identifying distinct phenotypes that are obfuscated when only analyzing population averages.

animal behavior and cognition↗

bioRxiv2022

Potent activation of NAD+-dependent deacetylase Sirt7 by nucleosome binding

Sirtuin-7 (Sirt7) is a nuclear NAD+-dependent deacetylase with a broad spectrum of biological functions. Sirt7 overexpression is linked to several pathological states and enhances anticancer drug resistance, making the enzyme a promising target for the development of novel therapeutics. Despite a plethora of reported in vivo functions the biochemical characterization of recombinant Sirt7 remains inadequate for the development of novel drug candidates. Here, we conduct an extensive biochemical analysis of Sirt7 using newly developed binding and kinetic assays to reveal that the enzyme preferentially interacts with and is activated by nucleosomes. Sirt7 activation by nucleic acids alone is effective towards long-chain acylated hydrophobic substrates while only nucleosome binding leads to 105-fold activation of deacetylase activity. Using endogenous chromatin and recombinant acetylated nucleosomes, we reveal that Sirt7 is one of the most efficient deacetylases in the sirtuin family and that its catalytic activity is limited by the rate of dissociation from deacetylated nucleosomes.

biochemistry↗

bioRxiv2022

IRF4 deficiency vulnerates B cell progeny for leukemogenesis via somatically acquired Jak3 mutations conferring IL-7 hypersensitivity

The processes leading from disturbed B cell development to adult B cell progenitor acute lymphoblastic leukemia (BCP-ALL) are poorly understood. Here, we describe Irf4-/- mice as prone to developing BCP-ALL with age. Irf4-/- preB-I cells exhibited impaired differentiation but enhanced proliferation in response to IL-7, along with reduced retention in the IL-7 providing bone marrow niche due to decreased CXCL12 responsiveness. Thus selected, preB-I cells acquired Jak3 mutations, probably following irregular AID activity, resulting in malignant transformation. We demonstrate heightened IL-7 sensitivity due to Jak3 mutants, devise a model to explain it and describe structural and functional similarities to Jak2 mutations often occurring in human Ph-like ALL. Finally, targeting JAK signaling with Ruxolitinib in vivo prolonged survival of mice bearing established Irf4-/- leukemia. Intriguingly, organ infiltration including leukemic meningeosis was selectively reduced without affecting blood blast counts. In this work, we present spontaneous leukemogenesis following IRF4 deficiency with potential implications for high-risk BCP-ALL in adult humans.

cancer biology↗

bioRxiv2021

Uncovering the Genetic Architecture of Broad Antisocial Behavior through a Genome-Wide Association Study Meta-analysis.

Despite the substantial heritability of antisocial behavior (ASB), specific genetic variants robustly associated with the trait have not been identified. The present study by the Broad Antisocial Behavior Consortium (BroadABC) meta-analyzed data from 28 discovery samples (N = 85,359) and five independent replication samples (N = 8,058) with genotypic data and broad measures of ASB. We identified the first significant genetic associations with broad ASB, involving common intronic variants in the forkhead box protein P2 (FOXP2) gene (lead SNP rs12536335, P = 6.32 x 10-10). Furthermore, we observed intronic variation in Foxp2 and one of its targets (Cntnap2) distinguishing a mouse model of pathological aggression (BALB/cJ strain) from controls (BALB/cByJ strain). The SNP-based heritability of ASB was 8.4% (s.e.= 1.2%). Polygenic-risk-score (PRS) analyses in independent samples revealed that the genetic risk for ASB was associated with several antisocial outcomes across the lifespan, including diagnosis of conduct disorder, official criminal convictions, and trajectories of antisocial development. We found substantial genetic correlations of ASB with mental health (depression rg{square}={square}0.63, insomnia rg = 0.47), physical health (overweight rg = 0.19, waist-to-hip ratio rg = 0.32), smoking (rg{square}={square}0.54), cognitive ability (intelligence rg= -0.40), educational attainment (years of schooling rg = -0.46) and reproductive traits (age at first birth rg={square}- 0.58, fathers age at death rg= -0.54). Our findings provide a starting point towards identifying critical biosocial risk mechanisms for the development of ASB.

genetics↗

bioRxiv2021

Mechanical vibration patterns elicit behavioral transitions and habituation in crawling Drosophila larvae

How animals respond to repeatedly applied stimuli, and how animals respond to mechanical stimuli in particular, are important questions in behavioral neuroscience. We study adaptation to repeated mechanical agitation using the Drosophila larva. Vertical vibration stimuli elicit a discrete set of responses in crawling larvae: continuation, pause, turn, and reversal. Through high-throughput larva tracking, we characterize how the likelihood of each response depends on vibration intensity and on the timing of repeated vibration pulses. By examining transitions between behavioral states at the population and individual levels, we investigate how the animals habituate to the stimulus patterns. We identify time constants associated with desensitization to prolonged vibration, with re-sensitization during removal of a stimulus, and additional layers of habituation that operate in the overall response. Known memory-deficient mutants exhibit distinct behavior profiles and habituation time constants. An analogous simple electrical circuit suggests possible neural and molecular processes behind adaptive behavior.

animal behavior and cognition↗

bioRxiv2021

Squidpy: a scalable framework for spatial single cell analysis

Spatial omics data are advancing the study of tissue organization and cellular communication at an unprecedented scale. Here, we present Squidpy, a Python framework that brings together tools from omics and image analysis to enable scalable description of spatial molecular data, such as transcriptome or multivariate proteins. Squidpy provides both infrastructure and numerous analysis methods that allow to efficiently store, manipulate and interactively visualize spatial omics data.

bioinformatics↗

bioRxiv2021

Expansion of cortical layers 2 and 3 in human left temporal cortex associates with verbal intelligence

The expansion of supragranular cortical layers is thought to have enabled evolutionary development of human cognition and language. However, whether increased volume of supragranular cortical layers can actually support greater cognitive and language abilities in humans has not been demonstrated. Here, we find that subjects with higher general and verbal intelligence test (VIQ) scores have selectively expanded layers 2 and 3 only in the left temporal cortex, an area associated with language and IQ-test performance. This expansion is accompanied by lower neuron densities and larger cell-body size. Furthermore, individuals with higher VIQ scores had neurons with larger dendritic trees in left temporal cortex, potentially impacting their function. Indeed, neurons of subjects with higher VIQ scores had faster action potential upstroke kinetics, which improves information processing. These data show that expansion of supragranular layer volume, cortical and cellular micro-architecture and function are associated with improved verbal mental ability in human subjects.

neuroscience↗

bioRxiv2021

Neuronal morphology and physiology, functional brain networks and memory in temporal lobe epilepsy

Temporal lobe epilepsy (TLE) patients are at risk of memory deficits, which have been linked to functional network disturbances, particularly of integration of the default mode network (DMN). However, the cellular substrates of functional network integration are unknown. We leverage a unique cross-scale dataset of therapy-resistant TLE patients, who underwent fMRI, MEG and/or neuropsychological testing before neurosurgery. fMRI and MEG underwent atlas-based connectivity analyses. Functional network centrality of the lateral middle temporal gyrus, part of the DMN, was used as a measure of local network integration. Subsequently, non-pathological cortical tissue from this region was used for single cell morphological and electrophysiological patch-clamp analysis, assessing integration in terms of total dendritic length and action potential rise speed. As could be hypothesized, greater network centrality related to better memory performance. Moreover, greater network centrality correlated with more integrative properties at the cellular level across patients. We conclude that individual differences in cognitively relevant functional network integration of a DMN region are mirrored by differences in cellular integrative properties of this region in TLE patients. These findings connect previously separate scales of investigation, increasing translational insight into focal pathology and large-scale network disturbances in TLE.

neuroscience↗

bioRxiv2021

Extracellular Matrix Dysfunction in Sorsby Patient-Derived Retinal Pigment Epithelium

Sorsby Fundus Dystrophy (SFD) is a rare form of macular degeneration that is clinically similar to age-related macular degeneration (AMD), and a histologic hallmark of SFD is a thick layer of extracellular deposits beneath the retinal pigment epithelium (RPE). Previous studies of SFD patient-induced pluripotent stem cell (iPSC) derived RPE differ as to whether these cultures recapitulate this key clinical feature by forming increased drusenoid deposits. The primary purpose of this study is to examine whether SFD patient-derived iPSC-RPE form basal deposits similar to what is found in affected family member SFD globes and to determine whether SFD iPSC RPE may be more oxidatively stressed. We performed a careful comparison of iPSC RPE from three control individuals, multiple iPSC clones from two SFD patients iPSC RPE, and post-mortem eyes of affected SFD family members. We also examined the effect of CRISPR-Cas9 gene correction of the S204C TIMP3 mutation on RPE phenotype. Finally, targeted metabolomics analysis with liquid chromatography and mass spectrometry analysis and stable isotope-labeled metabolite analysis was performed to determine whether SFD RPE are more oxidatively stressed. We found that SFD iPSC-RPE formed significantly more sub-RPE deposits ([~]6-90 m in height) compared to control RPE at 8 weeks. These deposits were similar in composition to the basal laminar drusen found in SFD family member globes by immunofluorescence staining and TEM imaging. S204C TIMP3 correction by CRISPR-Cas9 gene editing in SFD iPSC RPE cells resulted in significantly reduced basal laminar and sub-RPE calcium deposits. We detected a [~]18-fold increase in TIMP3 accumulation in the extracellular matrix (ECM) of SFD RPE, and targeted metabolomics showed that intracellular 4-hydroxyproline, a major breakdown product of collagen, is significantly elevated in SFD RPE, suggesting increased ECM turnover. Finally, SFD RPE cells have decreased intracellular reduced glutathione and were found to be more vulnerable to oxidative stress. Our findings suggest that elements of SFD pathology can be demonstrated in culture which may lead to insights into disease mechanisms.

cell biology↗

bioRxiv2020

Structural basis for the association of PLEKHA7 with membrane-embedded phosphatidylinositol lipids

PLEKHA7 (pleckstrin homology domain containing family A member 7) plays key roles in intracellular signaling, cytoskeletal organization and cell adhesion, and is associated with multiple human cancers. The interactions of its pleckstrin homology (PH) domain with membrane phosphatidyl-inositol-phosphate (PIP) lipids, are critical for proper cellular localization and function, and their inhibition is an attractive target for anti-cancer therapy. While structural data can provide insights in this area, little is known about the way in which PLEKHA7 and other PH domains interact with membrane-embedded PIPs. Here we report atomic-resolution structures of the PLEHA7 PH domain and describe the molecular mechanism for its recognition of membrane-bound PIPs. Using X-ray crystallography, nuclear magnetic resonance (NMR), molecular dynamics (MD) simulations, and isothermal titration calorimetry (ITC), we show - in atomic-level detail - that the interaction of PLEKHA7 with PIPs is multivalent and induces PIP clustering. The PIP binding mechanism is distinct from a discrete one-to-one interaction. Our findings reveal a central role of the membrane assembly in mediating protein-PIP association and provide a roadmap for the design of PLEKHA7-PIP inhibitors.

biochemistry↗

bioRxiv2020

CellRank for directed single-cell fate mapping

Computational trajectory inference enables the reconstruction of cell-state dynamics from single-cell RNA sequencing experiments. However, trajectory inference requires that the direction of a biological process is known, largely limiting its application to differentiating systems in normal development. Here, we present CellRank (https://cellrank.org) for mapping the fate of single cells in diverse scenarios, including perturbations such as regeneration or disease, for which direction is unknown. Our approach combines the robustness of trajectory inference with directional information from RNA velocity, derived from ratios of spliced to unspliced reads. CellRank takes into account both the gradual and stochastic nature of cellular fate decisions, as well as uncertainty in RNA velocity vectors. On data from pancreas development, we show that it automatically detects initial, intermediate and terminal populations, predicts fate potentials and visualizes continuous gene expression trends along individual lineages. CellRank also predicts a novel dedifferentiation trajectory during regeneration after lung injury, which we follow up experimentally by confirming the existence of previously unknown intermediate cell states.

bioinformatics↗

bioRxiv2020

Wild flies hedge their thermal preference bets in response to seasonal fluctuations

Fluctuating environmental pressures can challenge organisms by repeatedly shifting the optimum phenotype. Two contrasting evolutionary strategies to cope with these fluctuations are 1) evolution of the mean phenotype to follow the optimum (adaptive tracking) or 2) diversifying phenotypes so that at least some individuals have high fitness in the current fluctuation (bet-hedging). Bet-hedging could underlie stable differences in the behavior of individuals that are present even when genotype and environment are held constant. Instead of being simply noise, behavioral variation across individuals may reflect an evolutionary strategy of phenotype diversification. Using geographically diverse wild-derived fly strains and high-throughput assays of individual preference, we tested whether thermal preference variation in Drosophila melanogaster could reflect a bet-hedging strategy. We also looked for evidence that populations from different regions differentially adopt bet-hedging or adaptive-tracking strategies. Computational modeling predicted regional differences in the relative advantage of bet-hedging, and we found patterns consistent with that in regional variation in thermal preference heritability. In addition, we found that temporal patterns in mean preference support bet-hedging predictions and that there is a genetic basis for thermal preference variability. Our empirical results point to bet-hedging in thermal preference as a potentially important evolutionary strategy in wild populations.

evolutionary biology↗

bioRxiv2020

Genetic influences on hub connectivity of the human connectome

Brain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted imaging in twins, we identify a major role for genes, showing that they preferentially influence connectivity strength between network hubs of the human connectome. Using transcriptomic atlas data, we show that connected hubs demonstrate tight coupling of transcriptional activity related to metabolic and cytoarchitectonic similarity. Finally, comparing over thirteen generative models of network growth, we show that purely stochastic processes cannot explain the precise wiring patterns of hubs, and that model performance can be improved by incorporating genetic constraints. Our findings indicate that genes play a strong and preferential role in shaping the functionally valuable, metabolically costly connections between connectome hubs.

neuroscience↗

bioRxiv2020

Skipping and sliding to optimize target search on protein-bound DNA and RNA

Rapidly finding a specific nucleic-acid sequences in a large pool of competing off-targets is a fundamental challenge overcome by all living systems. To optimize the search and beat the diffusion limit, it is known that searchers should spend time sliding along the nucleic-acid substrate. Still, such sliding generally has to contend with high levels of molecular crowding on the substrate, and it remains unclear what effect this has on optimal search strategies. Using mechanistic modelling informed by single-molecule data, we show how sliding combined with correlated short-ranged skips allow searchers to maintain search speed on densely crowded substrates. We determine the conditions of optimal search, which show that an optimized searchers always spend more than half its time skipping and sliding along the substrate. Applying our theory to single-molecule data, we determine that both human and bacterial Argonaute proteins alternate between sliding 10 nt and skipping 30 nt along the substrate. We show that this combination of skipping and sliding lengths allows the searcher to maintain search speeds largely unaffected by molecular roadblocks covering up to 70% of the substrate. Our novel combination of experimental and theoretical approach could also help elucidate how other systems ensure rapid search in crowded environments.

biophysics↗

bioRxiv2020

A mechanistic model improves off-target predictions and reveals the physical basis of SpCas9 fidelity

The S. pyogenes (Sp) Cas9 endonuclease is an important gene-editing tool. SpCas9 is directed to target sites via a single guide RNA (sgRNA). However, SpCas9 also binds and cleaves genomic off-target sites that are partially matched to the sgRNA. Here, we report a microscopic kinetic model that simultaneously captures binding and cleavage dynamics for SpCas9 and Sp-dCas9 in free-energy terms. This model not only outperforms state-of-the-art off-target prediction tools, but also details how Sp-Cas9s structure-function relation manifests itself in binding and cleavage dynamics. Based on the biophysical parameters we extract, our model predicts SpCas9s open, intermediate, and closed complex configurations and indicates that R-loop progression is tightly coupled with structural changes in the targeting complex. We show that SpCas9 targeting kinetics are tuned for extended sequence specificity while maintaining on-target efficiency. Our extensible approach can characterize any CRISPR-Cas nuclease - benchmarking natural and future high-fidelity variants against SpCas9; elucidating determinants of CRISPR fidelity; and revealing pathways to increased specificity and efficiency in engineered systems.

biophysics↗

bioRxiv2020

Dynamics of Brain Structure and its Genetic Architecture over the Lifespan

Human brain structure changes throughout our lives. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental, and neurodegenerative diseases. Here, we identified common genetic variants that affect rates of brain growth or atrophy, in the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal MRI data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene-set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and ageing.

genetics↗