Biology subjects

Klein, D.

Publications and source records attributed to Klein, D..

29 records · Page 2Linked to original sources

bioRxiv2023

Desynapsis in potato is caused by StMSH4 mutant alleles and leads to either highly uniform unreduced pollen or sterility

The balanced segregation of homologous chromosomes during meiosis is essential for fertility and is mediated by crossovers. A strong reduction of crossovers leads to desynapsis, a process in which pairing of homologous chromosomes is abolished before metaphase I. This results in a random segregation of univalent and the production of unbalanced and sterile gametes. However, if desynapsis is combined with another meiotic alteration that restitutes the first meiotic division, then uniform and balanced unreduced gametes, essentially composed of non-recombinant homologs, are produced. This mitosis-like division is of interest to breeders because it transmits most of the parental heterozygosity to the gametes. In potato, desynapsis is a recessive trait that was tentatively mapped to chromosome 8. In this article, we have fine-mapped the position of the desynapsis locus and identified StMSH4, an essential component of the class I crossover pathway, as the most likely candidate gene. A seven base-pair insertion in the second exon of StMSH4 was found to be associated with desynapsis in our mapping population. We also identified a second allele with a 3820 base-pair insertion and confirmed that both alleles cannot complement each other. Such non-functional alleles appeared to be common in potato cultivars. More than half of the varieties we tested are carriers of mutational load at the StMSH4 locus. With this new information, breeders can choose to remove desynaptic alleles from their germplasm to improve fertility or to use them to produce highly uniform unreduced gametes in alternative breeding schemes.

plant biology↗

bioRxiv2023

The Cortical Representation of Language Timescales is Shared between Reading and Listening

Language comprehension involves integrating low-level sensory inputs into a hierarchy of increasingly high-level features. Prior work studied brain representations of different levels of the language hierarchy, but has not determined whether these brain representations are shared between written and spoken language. To address this issue, we analyzed fMRI BOLD data recorded while participants read and listened to the same narratives in each modality. Levels of the language hierarchy were operationalized as timescales, where each timescale refers to a set of spectral components of a language stimulus. Voxelwise encoding models were used to determine where different timescales are represented across the cerebral cortex, for each modality separately. These models reveal that between the two modalities timescale representations are organized similarly across the cortical surface. Our results suggest that, after low-level sensory processing, language integration proceeds similarly regardless of stimulus modality.

neuroscience↗

bioRxiv2022

Modeling Single-Cell Dynamics Using Unbalanced Parameterized Monge Maps

Optimal Transport (OT) has proven useful to infer single-cell trajectories of developing biological systems by aligning distributions across time points. Recently, Parameterized Monge Maps (PMM) were introduced to learn the optimal map between two distributions. Here, we apply PMM to model single-cell dynamics and show that PMM fails to account for asymmetric shifts in cell state distributions. To alleviate this limitation, we propose Unbalanced Parameterised Monge Maps (UPMM). We first describe the novel formulation and show on synthetic data how our method extends discrete unbalanced OT to the continuous domain. Then, we demonstrate that UPMM outperforms well-established trajectory inference methods on real-world developmental single-cell data.

bioinformatics↗

bioRxiv2022

Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells

RNA velocity has been rapidly adopted to guide the interpretation of transcriptional dynamics in snapshot single-cell transcriptomics data. Current approaches for estimating and analyzing RNA velocity can empirically reveal complex dynamics but lack effective strategies for quantifying the uncertainty of the estimate and its overall applicability to the system of interest. Here, we present veloVI (velocity variational inference), a deep generative modeling framework for estimating RNA velocity. veloVI learns a gene-specific dynamical model of RNA metabolism and provides a transcriptome-wide quantification of velocity uncertainty. We show in a series of examples that veloVI compares favorably to previous approaches for inferring RNA velocity with improvements in fit to the data, consistency across transcriptionally similar cells, and stability across preprocessing pipelines for quantifying RNA abundance. Further, we demonstrate that properties unique to veloVI, such as posterior velocity uncertainty, can be used to assess the appropriateness of analysis with velocity to the data at hand. Finally, we highlight veloVI as a flexible framework for modeling transcriptional dynamics by adapting the underlying dynamical model to use time-dependent transcription rates.

bioinformatics↗

bioRxiv2022

Beyond the limits of the unassigned protist microbiome: inferring large-scale spatio-temporal patterns of marine parasites

Marine protists are major components of the oceanic microbiome that remain largely unrepresented in culture collections and genomic reference databases. The exploration of this uncharted protist diversity in oceanic communities relies essentially on studying genetic markers from the environment as taxonomic barcodes. Here we report that across 6 large scale spatio-temporal planktonic surveys, half of the genetic barcodes remain taxonomically unassigned at the genus level, preventing a fine ecological understanding for numerous protist lineages. Among them, parasitic Syndiniales (Dinoflagellata) appear as the least described protist group. We have developed a computational workflow, integrating diverse 18S rDNA gene metabarcoding datasets, in order to infer large-scale ecological patterns at 100% similarity of the genetic marker, overcoming the limitation of taxonomic assignment. From a spatial perspective, we identified 2 171 unassigned clusters exclusively shared between the Tropical/Subtropical Ocean and the Mediterranean Sea among all Syndiniales orders and 25 ubiquitous clusters shared within all the studied marine regions. From a temporal perspective, over 3 time-series, we highlighted 38 unassigned clusters that follow rhythmic patterns of recurrence and are the best indicators of parasite communitys variation. These clusters withhold potential as ecosystem change indicators, mirroring their associated host community responses. Our results underline the importance of Syndiniales in structuring planktonic communities through space and time, raising questions regarding host-parasite association specificity and the trophic mode of persistent Syndiniales, while providing an innovative framework for prioritizing unassigned protist taxa for further description.

genomics↗

bioRxiv2022

Potent and specific human monoclonal antibodies against SARS-CoV-2 Omicron variant by rapid mRNA immunization of humanized mice

The Omicron variant (B.1.1.529) of SARS-CoV-2 rapidly becomes dominant globally. Its extensive mutations confer severe efficacy reduction to most of existing antibodies or vaccines. Here, we developed RAMIHM, a highly efficient strategy to generate fully human monoclonal antibodies (mAbs), directly applied it with Omicron-mRNA immunization, and isolated three potent and specific clones against Omicron. Rapid mRNA immunization elicited strong anti-Omicron antibody response in humanized mice, along with broader anti-coronavirus activity. Customized single cell BCR sequencing mapped the clonal repertoires. Top-ranked clones collectively from peripheral blood, plasma B and memory B cell populations showed high rate of Omicron-specificity (93.3%) from RAMIHM-scBCRseq. Clone-screening identified three highly potent neutralizing antibodies that have low nanomolar affinity for Omicron RBD, and low ng/mL level IC50 in neutralization, more potent than majority of currently approved or authorized clinical RBD-targeting mAbs. These lead mAbs are fully human and ready for downstream IND-enabling and/or translational studies.

bioengineering↗

bioRxiv2022

Protein-Ligand Interaction Graphs: Learning from Ligand-Shaped 3D Interaction Graphs to Improve Binding Affinity Prediction

Graph Neural Networks (GNNs) have recently gained in popularity, challenging molecular fingerprints or SMILES-based representations as the predominant way to represent molecules for binding affinity prediction. Although simple ligand-based graphs alone are already useful for affinity prediction, better performance on multi-target datasets has been achieved with models that incorporate 3D structural information. Most recent advances utilize complex GNN architectures to capture 3D protein-ligand information by incorporating ligand-interacting protein atoms as additional nodes in the graphs; or by building a second protein-based graph in parallel. This expands the graph considerably while obfuscating the shape of the underlying ligand, diminishing the advantage that GNNs have when encoding molecular structures. There is therefore a need for a simple and elegant molecular graph representation that retains the topology of the ligand while simultaneously encoding 3D protein-ligand interactions. We present Protein-Ligand Interaction Graphs (PLIGs): a simple way of representing atom-atom contacts of 3D protein-ligand complexes as node features for GNNs. PLIGs featurize an atom node in the molecular graph by describing each atoms properties as well as all atom-atom contacts made with protein atoms within a distance threshold. The edges of the graph are therefore identical to ligand-based graphs, but the nodes encode the 3D protein-ligand contacts. Since PLIGs are applicable to any GNN architecture, we have benchmarked their performance with six different GNN architectures, and compared them to conventional ligand-based graphs and fingerprint-based multi-layer perceptron (MLP) models using the CASF-2016 benchmark set where we found PLIG-based Graph Attention Networks (GATNet) to be the best performing model ({rho}=0.84, RMSE=1.22 pK). In summary, we created a novel graph-based representation that incorporates 3D structural information into the node features of ligand-shaped molecular graphs. The PLIG representation is simple, elegant, flexible and easily customizable, opening up many possibilities of incorporating other 2D and 3D properties into the graph. AccessThe code and implementation for PLIGs and all models can be found at github.com/MarcMoesser/Protein-Ligand-Interaction-Graphs.

bioinformatics↗

bioRxiv2021

Monospecific and bispecific monoclonal SARS-CoV-2 neutralizing antibodies that maintain potency against B.1.617

COVID-19 pathogen SARS-CoV-2 has infected hundreds of millions and caused over 5 million deaths to date. Although multiple vaccines are available, breakthrough infections occur especially by emerging variants. Effective therapeutic options such as monoclonal antibodies (mAbs) are still critical. Here, we report the development, cryo-EM structures, and functional analyses of mAbs that potently neutralize SARS-CoV-2 variants of concern. By high-throughput single cell sequencing of B cells from spike receptor binding domain (RBD) immunized animals, we identified two highly potent SARS-CoV-2 neutralizing mAb clones that have single-digit nanomolar affinity and low-picomolar avidity, and generated a bispecific antibody. Lead antibodies showed strong inhibitory activity against historical SARS-CoV-2 and several emerging variants of concern. We solved several cryo-EM structures at [~]3 [A] resolution of these neutralizing antibodies in complex with prefusion spike trimer ectodomain, and revealed distinct epitopes, binding patterns, and conformations. The lead clones also showed potent efficacy in vivo against authentic SARS-CoV-2 in both prophylactic and therapeutic settings. We also generated and characterized a humanized antibody to facilitate translation and drug development. The humanized clone also has strong potency against both the original virus and the B.1.617.2 Delta variant. These mAbs expand the repertoire of therapeutics against SARS-CoV-2 and emerging variants.

immunology↗

bioRxiv2021

Genome-wide Disease Screening in Early Human Embryos with Primary Template-Directed Amplification

Current preimplantation genetic testing (PGT) enables the selection of embryos based on fetal aneuploidy or the presence a small number of preselected disease-associated variants. Here we present a new approach that takes advantage of the improved genome coverage and uniformity of primary template-directed amplification (PTA) to call most early embryo genetic variants accurately and reproducibly from a preimplantation biopsy. With this approach, we identified clonal and mosaic chromosomal aneuploidy, de novo mitochondrial variants, and variants predicted to cause mendelian and non-mendelian diseases. In addition, we utilized the genome-wide information to compute polygenic risk scores for common diseases. Although numerous computational, interpretive, and ethical challenges remain, this approach establishes the technical feasibility of screening for and preventing numerous debilitating inherited diseases.

bioengineering↗

bioRxiv2021

Temporal specificity of abnormal neural oscillations during phonatory events in Laryngeal Dystonia

Laryngeal Dystonia is a debilitating disorder of voicing in which the laryngeal muscles are intermittently in spasm resulting in involuntary interruptions during speech. The central pathophysiology of laryngeal dystonia, underlying computational impairments in vocal motor control, remains poorly understood. Although prior imaging studies have found aberrant activity in the central nervous system during phonation in patients with laryngeal dystonia, it is not known at what timepoints during phonation these abnormalities emerge and what function may be impaired. To investigate this question, we recruited 22 adductor laryngeal dystonia patients (15 female, age range = 28.83-72.46 years) and 18 controls (8 female, age range = 27.40-71.34 years). We leveraged the fine temporal resolution of magnetoencephalography to monitor neural activity around glottal movement onset, subsequent voice onset and after the onset of pitch feedback perturbations. We examined event-related beta-band (12-30 Hz) and high-gamma band (65-150 Hz) neural oscillations. Prior to glottal movement onset, we observed abnormal frontoparietal motor preparatory activity. After glottal movement onset, we observed abnormal activity in somatosensory cortex persisting through voice onset. Prior to voice onset and continuing after, we also observed abnormal activity in the auditory cortex and the cerebellum. After pitch feedback perturbation onset, we observed no differences between controls and patients in their behavioural responses to the perturbation. But in patients, we did find abnormal activity in brain regions thought to be involved in the auditory feedback control of vocal pitch (premotor, motor, somatosensory and auditory cortices). Our study results confirm the abnormal processing of somatosensory feedback that has been seen in other studies. However, there were several remarkable findings in our study. First, patients have impaired vocal motor activity even before glottal movement onset, suggesting abnormal movement preparation. These results are significant because: (i) they occur before movement onset, abnormalities in patients cannot be ascribed to deficits in vocal performance, and (ii) they show that neural abnormalities in laryngeal dystonia are more than just abnormal responses to sensory feedback during phonation as has been hypothesised in some previous studies. Second, abnormal auditory cortical activity in patients begins even before voice onset, suggesting abnormalities in setting up auditory predictions before the arrival of auditory feedback at voice onset. Generally, activation abnormalities identified in key brain regions within the speech motor network around various phonation events not only provide temporal specificity to neuroimaging phenotypes in laryngeal dystonia but also may serve as potential therapeutic targets for neuromodulation.

neuroscience↗

bioRxiv2020

Accurate Genomic Variant Detection in Single Cells with Primary Template-Directed Amplification

Improvements in whole genome amplification (WGA) would enable new types of basic and applied biomedical research, including studies of intratissue genetic diversity that require more accurate single-cell genotyping. Here we present primary template-directed amplification (PTA), a new isothermal WGA method that reproducibly captures >95% of the genomes of single cells in a more uniform and accurate manner than existing approaches, resulting in significantly improved variant calling sensitivity and precision. To illustrate the new types of studies that are enabled by PTA, we developed direct measurement of environmental mutagenicity (DMEM), a new tool for mapping genome-wide interactions of mutagens with single living human cells at base pair resolution. In addition, we utilized PTA for genome-wide off-target indel and structural variant detection in cells that had undergone CRISPR-mediated genome editing, establishing the feasibility for performing single-cell evaluations of biopsies from edited tissues. The improved precision and accuracy of variant detection with PTA overcomes the current limitations of accurate whole genome amplification, which is the major obstacle to studying genetic diversity and evolution at cellular resolution.

genomics↗