Naturally occurring and engineered flavin-binding, blue-light-sensing, light, oxygen, voltage (LOV) photoreceptor domains have been used widely to design fluorescent reporters, optogenetic tools, and ...photosensitizers for the visualization and control of biological processes. In addition, natural LOV photoreceptors with engineered properties were recently employed for optimizing plant biomass production in the framework of a plant-based bioeconomy. Here, the understanding and fine-tuning of LOV photoreceptor (kinetic) properties is instrumental for application. In response to blue-light illumination, LOV domains undergo a cascade of photophysical and photochemical events that yield a transient covalent FMN-cysteine adduct, allowing for signaling. The rate-limiting step of the LOV photocycle is the dark-recovery process, which involves adduct scission and can take between seconds and days. Rational engineering of LOV domains with fine-tuned dark recovery has been challenging due to the lack of a mechanistic model, the long time scale of the process, which hampers atomistic simulations, and a gigantic protein sequence space covering known mutations (combinatorial challenge). To address these issues, we used machine learning (ML) trained on scarce literature data and iteratively generated and implemented experimental data to design LOV variants with faster and slower dark recovery. Over the three prediction–validation cycles, LOV domain variants were successfully predicted, whose adduct-state lifetimes spanned 7 orders of magnitude, yielding optimized tools for synthetic (opto)biology. In summary, our results demonstrate ML as a viable method to guide the design of proteins even with limited experimental data and when no mechanistic model of the underlying physical principles is available.
Light, oxygen, voltage (LOV) photoreceptors are widely distributed throughout all kingdoms of life, and have in recent years, due to their modular nature, been broadly used as sensor domains for the ...construction of optogenetic tools. For understanding photoreceptor function as well as for optogenetic tool design and fine-tuning, a detailed knowledge of the photophysics, photochemistry, and structural changes underlying the LOV signaling paradigm is instrumental. Mutations that alter the lifetime of the photo-adduct signaling state represent a convenient handle to tune LOV sensor on/off kinetics and, thus, steady-state on/off equilibria of the photoreceptor (or optogenetic switch). Such mutations, however, should ideally only influence sensor kinetics, while being benign with regard to the nature of the structural changes that are induced by illumination, i.e., they should not result in a disruption of signal transduction. In the present study, we identify a conserved hydrophobic pocket for which mutations have a strong impact on the adduct-state lifetime across different LOV photoreceptor families. Using the slow cycling bacterial short LOV photoreceptor PpSB1-LOV, we show that the I48T mutation within this pocket, which accelerates adduct rupture, is otherwise structurally and mechanistically benign, i.e., light-induced structural changes, as probed by NMR spectroscopy and X-ray crystallography, are not altered in the variant. Additional mutations within the pocket of PpSB1-LOV and the introduction of homologous mutations in the LOV photoreceptor YtvA of
Bacillus subtilis
and the
Avena sativa
LOV2 domain result in similarly altered kinetics. Given the conserved nature of the corresponding structural region, the here identified mutations should find application in dark-recovery tuning of optogenetic tools and LOV photoreceptors, alike.
Graphical abstract
Photoactive biological systems modify the optical properties of their chromophores, known as spectral tuning. Determining the molecular origin of spectral tuning is instrumental for understanding the ...function and developing applications of these biomolecules. Spectral tuning in flavin-binding fluorescent proteins (FbFPs), an emerging class of fluorescent reporters, is limited by their dependency on protein-bound flavins, whose structure and hence electronic properties cannot be altered by mutation. A blue-shifted variant of the plant-derived improved light, oxygen, voltage FbFP has been created by introducing a lysine within the flavin-binding pocket, but the molecular basis of this shift remains unconfirmed. We here structurally characterize the blue-shifted improved light, oxygen, voltage variant and construct a new blue-shifted CagFbFP protein by introducing an analogous mutation. X-ray structures of both proteins reveal displacement of the lysine away from the chromophore and opening up of the structure as instrumental for the blue shift. Site saturation mutagenesis and high-throughput screening yielded a red-shifted variant, and structural analysis revealed that the lysine side chain of the blue-shifted variant is stabilized close to the flavin by a secondary mutation, accounting for the red shift. Thus, a single additional mutation in a blue-shifted variant is sufficient to generate a red-shifted FbFP. Using spectroscopy, X-ray crystallography, and quantum mechanics molecular mechanics calculations, we provide a firm structural and functional understanding of spectral tuning in FbFPs. We also show that the identified blue- and red-shifted variants allow for two-color microscopy based on spectral separation. In summary, the generated blue- and red-shifted variants represent promising new tools for application in life sciences.
Structural information on electronically excited neutral molecules can be indirectly retrieved, largely through pump–probe and rotational spectroscopy measurements with the aid of calculations. Here, ...we demonstrate the direct structural retrieval of neutral carbonyl disulfide (CS₂) in the B̃ ¹ B₂ excited electronic state using laser-induced electron diffraction (LIED).We unambiguously identify the ultrafast symmetric stretching and bending of the field-dressed neutral CS₂ molecule with combined picometer and attosecond resolution using intrapulse pump–probe excitation and measurement. We invoke the Renner–Teller effect to populate the B̃ ¹ B₂ excited state in neutral CS₂, leading to bending and stretching of the molecule. Our results demonstrate the sensitivity of LIED in retrieving the geometric structure of CS₂, which is known to appear as a two-center scatterer.
Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of ...variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe "DeepWAS", a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to 61 regulatory SNPs, called dSNPs, were associated with multiple sclerosis (MS, 4,888 cases and 10,395 controls), major depressive disorder (MDD, 1,475 cases and 2,144 controls), and height (5,974 individuals). These variants were mainly non-coding and reached at least nominal significance in classical GWAS. The prediction accuracy was higher for DeepWAS than for classical GWAS models for 91% of the genome-wide significant, MS-specific dSNPs. DSNPs were enriched in public or cohort-matched expression and methylation quantitative trait loci and we demonstrated the potential of DeepWAS to generate testable functional hypotheses based on genotype data alone. DeepWAS is available at https://github.com/cellmapslab/DeepWAS.
Long time series of reliable individual growth estimates are crucial for understanding the status of a fish stock and deciding upon appropriate management. Tagging data provide valuable information ...about fish growth, and are especially useful when age‐based growth estimates and stock assessments are compromised by age‐determination uncertainties. However, in the literature there is a lack of studies assessing possible changes in growth over time using tagging data. Here, data from tagging experiments performed in the Baltic Sea between 1971 and 2019 were added to those previously analysed for 1955–1970 to build the most extensive tagging dataset available for Eastern Baltic cod (Gadus morhua, Gadidae), a threatened stock with severe age‐determination problems. Two length‐based methods, the GROTAG model (based on the von Bertalanffy growth function) and a Generalized Additive Model, were used to assess for the first time the potential long‐term changes in cod growth using age‐independent data. Both methods showed strong changes in growth with an increase until the end of the 1980s (8.6–10.6 cm/year for a 40 cm cod depending on the model) followed by a sharp decline. This study also revealed that the current growth of cod is the lowest observed in the past 7 decades (4.3–5.1 cm/year for a 40 cm cod depending on the model), indicating very low productivity. This study provides the first example of the use of tagging data to estimate multidecadal changes in growth rates in wild fish. This methodology can also be applied to other species, especially in those cases where severe age‐determination problems exist.
A major evolution from purely clinical diagnoses to biomarker supported clinical diagnosing has been occurring over the past years in neurology. High-throughput methods, such as next-generation ...sequencing and mass spectrometry-based proteomics along with improved neuroimaging methods, are accelerating this development. This calls for a consensus framework that is broadly applicable and provides a spot-on overview of the clinical validity of novel biomarkers. We propose a harmonized terminology and a uniform concept that stratifies biomarkers according to clinical context of use and evidence levels, adapted from existing frameworks in oncology with a strong focus on (epi)genetic markers and treatment context. We demonstrate that this framework allows for a consistent assessment of clinical validity across disease entities and that sufficient evidence for many clinical applications of protein biomarkers is lacking. Our framework may help to identify promising biomarker candidates and classify their applications by clinical context, aiming for routine clinical use of (protein) biomarkers in neurology.
Abstract
In multiple myeloma spatial differences in the subclonal architecture, molecular signatures and composition of the microenvironment remain poorly characterized. To address this shortcoming, ...we perform multi-region sequencing on paired random bone marrow and focal lesion samples from 17 newly diagnosed patients. Using single-cell RNA- and ATAC-seq we find a median of 6 tumor subclones per patient and unique subclones in focal lesions. Genetically identical subclones display different levels of spatial transcriptional plasticity, including nearly identical profiles and pronounced heterogeneity at different sites, which can include differential expression of immunotherapy targets, such as CD20 and CD38. Macrophages are significantly depleted in the microenvironment of focal lesions. We observe proportional changes in the T-cell repertoire but no site-specific expansion of T-cell clones in intramedullary lesions. In conclusion, our results demonstrate the relevance of considering spatial heterogeneity in multiple myeloma with potential implications for models of cell-cell interactions and disease progression.
The human leukocyte antigen (HLA) haplotype DRB1*15:01 is the major risk factor for multiple sclerosis (MS). Here, we find that DRB1*15:01 is hypomethylated and predominantly expressed in monocytes ...among carriers of DRB1*15:01. A differentially methylated region (DMR) encompassing HLA-DRB1 exon 2 is particularly affected and displays methylation-sensitive regulatory properties in vitro. Causal inference and Mendelian randomization provide evidence that HLA variants mediate risk for MS via changes in the HLA-DRB1 DMR that modify HLA-DRB1 expression. Meta-analysis of 14,259 cases and 171,347 controls confirms that these variants confer risk from DRB1*15:01 and also identifies a protective variant (rs9267649, p < 3.32 × 10−8, odds ratio = 0.86) after conditioning for all MS-associated variants in the region. rs9267649 is associated with increased DNA methylation at the HLA-DRB1 DMR and reduced expression of HLA-DRB1, suggesting a modulation of the DRB1*15:01 effect. Our integrative approach provides insights into the molecular mechanisms of MS susceptibility and suggests putative therapeutic strategies targeting a methylation-mediated regulation of the major risk gene.
PDF
