Biology subjects

Lange, B.

Publications and source records attributed to Lange, B..

8 recordsLinked to original sources

bioRxiv2025

Rapid Cell-Free Combinatorial Mutagenesis Workflow Using Small Oligos Suitable for High-Iteration, Active Learning-Guided Protein Engineering

Active learning-guided protein engineering e2iciently navigates the challenging fitness landscape by screening designs iteratively in a model-guided design-build-test-learn cycle. However, while high iterations boost performance, current workflows reliance on tedious and costly cell-based cloning and expression steps limits the iterations they can practically implement. To address this problem, we present a novel combinatorial mutagenesis workflow that uses small ([~]20-40 bp) mutagenic annealed-oligo fragments and cell-free expression to rapidly and conveniently screen protein variants in <9 hours. Using bulk-prepared mutagenic oligos eliminates the need for cloning, PCR-based mutagenesis, or ordering costly genes each screening round. Their >80% size reduction from current fragment-based shu2ling strategies also helps avoid including multiple mutations on the same fragment, reducing the number one must order to cover the design space. By screening 3-10 fragment assemblies for two di2erent proteins, we show our approach is a general, scalable, and cost-e2ective platform for high-iteration protein engineering.

bioengineering↗

bioRxiv2024

A quantitative framework for structural interpretation of DMS reactivity

Dimethyl sulfate (DMS) chemical mapping probes RNA structure, where low reactivity is generally interpreted as Watson-Crick (WC) base pairs and high reactivity as unpaired nucleotides. Studies examining DMS reactivity of RNAs with known 3D structures have identified nucleotides that deviate from this interpretation with distinct solvent accessibility and hydrogen bonding patterns. Understanding the frequency of these outliers and their recurring structural 3D features remains incomplete. To address this knowledge gap, we systematically analyzed DMS reactivity patterns across a library of 7,500 RNA constructs containing two-way junctions with known 3D structures. We observe DMS reactivity exists on a continuum over four orders of magnitude with approximately 10% overlap in reactivity between WC and non-WC nucleotides. We find that non-WC bases with WC-like DMS protection exhibit increased hydrogen bonding and decreased solvent accessibility, whereas WC pairs exhibiting greater DMS reactivity tend to flank junctions, correlating with weaker base stacking and greater junction dynamics. Furthermore, we discover that DMS reactivity values in non-canonical pairs correlate with atomic distances and base pair geometry, enabling discrimination between different 3D conformations. These DMS reactivity patterns indicate that DMS reactivity provides atomic-scale information about RNA 3D conformations, which can be used to model RNA structures and dynamics.

biochemistry↗

bioRxiv2024

Soybean phenotypic plasticity in response to dark chilling stress

The expansion of soybean cultivation to high-latitude regions is hindered by the adverse effects of dark chilling stress. This study investigates the phenotypic plasticity of soybean in response to dark chilling stress, aiming to identify traits that contribute to adaptation in northern climates. Five soybean cultivars from early maturity groups (000 and 00) were grown in growth chambers set either at 25/18{degrees}C or 25/10{degrees}C (day/night), and a range of performance and functional traits were measured. The relative distance plasticity index highlighted variations in plasticity across traits and genotypes. Photosynthetic activity recovery traits, shoot growth rate, and tap root elongation rate showed high plasticity and significant differences between cultivars, making them suitable for assessing dark chilling tolerance. Moreover, distinct responses to dark chilling stress were exhibited by different soybean cultivars. For instance, cv. SOPRANA displayed a greater phenotypic plasticity in aboveground performance traits, such as shoot growth, while cv. SULTANA exhibited a greater plasticity in physiological traits like photosynthetic activity recovery. These differing strategies may lead to similar biomass production through distinct mechanisms, highlighting the complexity of soybeans adaptive responses to dark chilling stress. These findings provide valuable insights for breeders seeking to develop soybean cultivars adapted to high latitudes, meeting the increasing demand for locally produced protein-based food. However, further research in real field conditions is essential to validate the potential benefits of these plastic traits and their role in improving soybean resilience to dark chilling stress. The identified plastic traits offer a promising avenue for screening a broader range of cultivars and enhancing soybeans suitability for cultivation in northern regions.

plant biology↗

bioRxiv2023

Development and validation of a respiratory syncytial virus multiplex immunoassay

Respiratory syncytial virus (RSV) is one of the leading causes of severe respiratory disease in infants and adults. RSV exists as two subtypes A and B, which co-circulate throughout the season, although one will usually become dominant. While vaccines and monoclonal therapeutic antibodies either are or will shortly become available, correlates of protection remain unclear. For this purpose, we developed an RSV multiplex immunoassay that analyses antibody titers towards the post-F, Nucleoprotein, and a diverse mix of G proteins. Technical and clinical validation showed outstanding performance, while methodological developments enabled identification of the subtype of previous infections through use of the diverse G proteins for approximately 50% of samples. As a proof of concept to show the suitability of the assay in serosurveillance studies, we then evaluated titer decay and age- dependent antibody responses within population cohorts. Overall, the developed assay shows robust performance, is scalable, provides additional information on infection subtype, and is therefore ideally suited to be used in future population cohort studies. ImportanceAlthough respiratory syncytial virus (RSV) is endemic and re-infections are common and harmless to the majority of the population, it is a leading cause of hospitalization in young children, the elderly, or immunocompromised individuals. A better characterization of RSV immunology and spreading dynamics is thus critical for preparedness, especially when interventions aiming to mitigate other diseases (e.g., COVID-19) disturb its endemic cycles. This requires high-throughput information-dense assays. We therefore developed a bead-based multiplex immunoassay that allows measurements of antibodies against multiple RSV antigens simultaneously. We identified antibodies which were strong indicators of previous infection, while others allowed identification of the subtype of the previous infection. The assay itself was shown to be robust and scalable, making it ideal for to keep track of the temporal variation RSV immunity profiles within the population.

immunology↗

bioRxiv2023

Visualizing a two-state conformational ensemble in stem-loop 3 of the transcriptional regulator 7SK RNA

Structural plasticity is integral to RNA function; however, there are currently few methods to quantitatively resolve RNAs that have multiple structural states. NMR spectroscopy is a powerful approach for resolving conformational ensembles but is size-limited. Chemical probing is well-suited for large RNAs but provides limited structural and no kinetics information. Here, we integrate the two approaches to visualize a two-state conformational ensemble for the central stem-loop 3 (SL3) of 7SK RNA, a critical element for 7SK RNA function in transcription regulation. We find that the SL3 distal end exchanges between two equally populated yet structurally distinct states in both isolated SL3 constructs and full-length 7SK RNA. We rationally designed constructs that lock SL3 into a single state and demonstrate that both chemical probing and NMR data fit to a linear combination of the two states. Comparison of vertebrate 7SK RNA sequences shows conservation of both states, suggesting functional importance. These results provide new insights into 7SK RNA structural dynamics and demonstrate the utility of integrating chemical probing with NMR spectroscopy to gain quantitative insights into RNA conformational ensembles.

biophysics↗

bioRxiv2020

A fine-tuned interplay of three A. thaliana UDP glucosyltransferases orchestrates salicylic acid homeostasis

Salicylic acid (SA) is a central signaling molecule in development and defense, therefore its levels are tightly controlled. One control mechanism is conjugation with sugar moieties by UDP glucosyltransferases (UGTs). In Arabidopsis, UGT76B1, UGT74F1, and UGT74F2 are known to glucosylate SA. We show that these are the main SA UGTs in leaves, since only marginal levels of SA glucosides were found in a triple loss-of-function mutant. Analyzing transcriptomes, metabolite levels, and phenotypes of a full combinatorial set of loss-of-function mutants, we resolved the mutual relationships and the individual roles of these enzymes in SA homeostasis. The strongest gene expression changes were observed for the ugt76b1 ugt74f1 double mutant, which downregulated developmental genes and most pronouncedly upregulated cell death-related genes. Among the single mutants, ugt76b1 specifically exhibited increased production of reactive oxygen species, increased resistance to infection, and early senescence. Likewise, higher-order mutations confirmed the dominant role of UGT76B1 in controlling SA levels and thereby the expression of biotic stress response genes. Both UGT74F1 and UGT74F2 affected UGT76B1 expression. However, while UGT76B1 and UGT74F1 produced SA-2-O-{beta}-glucoside, UGT74F2 did not contribute there substantially. Instead, UGT74F2 acted independently of UGT74F1, decreasing steady-state SA levels by producing salicyloyl glucose ester. Remarkably, this did not restrict defense responses. In contrast, UGT74F1 interacted with UGT76B1 in suppressing defense responses. Nevertheless, a benzothiadiazole-triggered defense scenario induced only UGT76B1, whereas UGT74F1 was linked to controlling abiotic stress responses. All three enzymes form a network that, in concert with other UGTs, regulates expression of developmental and stress-related genes. One sentence summaryThe salicylic acid glucosylating enzymes of Arabidopsis leaves are crucial for salicylic acid homeostasis and combinatorially impact defense responses and developmental processes.

plant biology↗

bioRxiv2019

Mini-batch optimization enables training of ODE models on large-scale datasets

Quantitative dynamical models are widely used to study cellular signal processing. A critical step in modeling is the estimation of unknown model parameters from experimental data. As model sizes and datasets are steadily growing, established parameter optimization approaches for mechanistic models become computationally extremely challenging. However, mini-batch optimization methods, as employed in deep learning, have better scaling properties. In this work, we adapt, apply, and benchmark mini-batch optimization for ordinary differential equation (ODE) models thereby establishing a direct link between dynamic modeling and machine learning. On our main application example, a large-scale model of cancer signaling, we benchmark mini-batch optimization against established methods, achieving better optimization results and reducing computation by more than an order of magnitude. We expect that our work will serve as a first step towards mini-batch optimization tailored to ODE models and enable modeling of even larger and more complex systems than what is currently possible.

systems biology↗

bioRxiv2017

Efficient parameterization of large-scale mechanistic models enables drug response prediction for cancer cell lines

The response of cancer cells to drugs is determined by various factors, including the cells mutations and gene expression levels. These factors can be assessed using next-generation sequencing. Their integration with vast prior knowledge on signaling pathways is, however, limited by the availability of mathematical models and scalable computational methods. Here, we present a computational framework for the parameterization of large-scale mechanistic models and its application to the prediction of drug response of cancer cell lines from exome and transcriptome sequencing data. With this framework, we parameterized a mechanistic model describing major cancer-associated signaling pathways (>1200 species and >2600 reactions) using drug response data. For the parameterized mechanistic model, we found a prediction accuracy, which exceeds that of the considered statistical approaches. Our results demonstrate for the first time the massive integration of heterogeneous datasets using large-scale mechanistic models, and how these models facilitate individualized predictions of drug response. We anticipate our parameterized model to be a starting point for the development of more comprehensive, curated models of signaling pathways, accounting for additional pathways and drugs.

systems biology↗