Publications

Motivated by the question of how biological systems maintain homeostasis in changing environments, Shinar and Feinberg introduced in 2010 the concept of absolute concentration robustness (ACR). A biochemical system exhibits ACR in some species if the steady-state value of that species does not depend on initial conditions. Thus, a system with ACR can maintain a constant level of one species even as the initial condition changes. Despite a great deal of interest in ACR in recent years, the following basic question remains open: How can we determine quickly whether a given biochemical system has ACR? Although various approaches to this problem have been proposed, we show that they are incomplete. Accordingly, we present new methods for deciding ACR, which harness computational algebra. We illustrate our results on several biochemical signaling networks.

Tight junctions play an essential role in sealing tissues, by forming belts of adhesion strands around cellular perimeters. Recent work has shown that the condensation of ZO1 scaffold proteins is required for tight junction assembly. However, the mechanisms by which junctional condensates initiate at cell-cell contacts and elongate around cell perimeters remain unknown. Combining biochemical reconstitutions and live-cell imaging of MDCKII tissue, we found that tight junction belt formation is driven by adhesion receptor-mediated ZO1 surface condensation coupled to local actin polymerization. Adhesion receptor oligomerization provides the signal for surface binding and local condensation of ZO1 at the cell membrane. Condensation produces a molecular scaffold that selectively enriches junctional proteins. Finally, ZO1 condensates directly facilitate local actin polymerization and filament bundling, driving the elongation into a continuous tight junction belt. More broadly, our work identifies how cells couple surface condensation with cytoskeleton organization to assemble and structure adhesion complexes.

Prolonged hospital waiting times are linked with increased patient mortality and cause additional financial burdens on institutions. Efficient point-of-care diagnosis would help alleviate this, but is hampered by a lack of cost-effective devices capable of rapid, in situ, wide ranging analyte detection. Lab-on-fiber technology provides an answer allowing for diagnosis, treatment, and monitoring in situ with real time feedback. Here, a device is demonstrated that harnesses motor-protein-driven-microtubule molecular detection assays to optical fibers. By developing a new method for microscope-free microtubule gliding speed determination, proof of concept is demonstrated in the detection of Monomeric Streptavidin and Neutravidin, which initiate a decrease in speed in biotinylated microtubules as well as bundling in the latter case. Utilizing antibody functionalizsed microtubules label-free and microscope-free detection of the heart attack marker Creatine Kinase-MB, as well secondary antibodies in nm concentration is demonstrated. This detector has the potential to be used in situ, providing rapid, low-cost, multiplex analyte screening and detection.

The recent AI breakthrough of AlphaFold2 has revolutionized 3D protein structural modeling, proving crucial for protein design and variant effects prediction. However, intrinsically disordered regions-known for their lack of well-defined structure and lower sequence conservation-often yield low-confidence models. The latest Variant Effect Predictor (VEP), AlphaMissense, leverages AlphaFold2 models, achieving over 90% sensitivity and specificity in predicting variant effects. However, the effectiveness of tools for variants in disordered regions, which account for 30% of the human proteome, remains unclear.

Considerable phenotypic variation under identical culture conditions limits the potential of stem-cell-based embryo models (SEMs) in basic and applied research. The biological processes causing this seemingly stochastic variation remain unclear. Here, we investigated the roots of phenotypic variation by parallel recording of transcriptomic states and morphological history in individual structures modeling embryonic trunk formation. Machine learning and integration of time-resolved single-cell RNA sequencing with imaging-based phenotypic profiling identified early features predictive of phenotypic end states. Leveraging this predictive power revealed that early imbalance of oxidative phosphorylation and glycolysis results in aberrant morphology and a neural lineage bias, which we confirmed by metabolic measurements. Accordingly, metabolic interventions improved phenotypic end states. Collectively, our work establishes divergent metabolic states as drivers of phenotypic variation and offers a broadly applicable framework to chart and predict phenotypic variation in organoids and SEMs. The strategy can be used to identify and control underlying biological processes, ultimately increasing reproducibility.

Metabolic pathways can influence cell fate decisions, yet their regulative role during embryonic development remains poorly understood. Here, we demonstrate an instructive role of glycolytic activity in regulating signaling pathways involved in mesoderm and endoderm specification. Using a mouse embryonic stem cell (mESC)-based in vitro model for gastrulation, we found that glycolysis inhibition increases ectodermal cell fates at the expense of mesodermal and endodermal lineages. We demonstrate that this relationship is dose dependent, enabling metabolic control of germ layer proportions through exogenous glucose levels. We further show that glycolysis acts as an upstream regulator of Nodal and Wnt signaling and that its influence on cell fate specification can be decoupled from its effects on growth. Finally, we confirm the generality of our findings using a human gastrulation model. Our work underscores the dependence of signaling pathways on metabolic conditions and provides mechanistic insight into the nutritional regulation of cell fate decision-making.

Familial adenomatous polyposis (FAP) is caused by pathogenic germline variants in the tumor suppressor gene APC. Confirmation of diagnosis was not achieved by cancer gene panel and exome sequencing or custom array-CGH in a family with suspected FAP across five generations. Long-read genome sequencing (PacBio), short-read genome sequencing (Illumina), short-read RNA sequencing, and further validations were performed in different tissues of multiple family members. Long-read genome sequencing resolved a 6 kb full-length intronic insertion of a heterozygous LINE-1 element between exons 7 and 8 of APC that could be detected but not fully resolved by short-read genome sequencing. Targeted RNA analysis revealed aberrant splicing resulting in the formation of a pseudo-exon with a premature stop codon. The variant segregated with the phenotype in several family members allowing its evaluation as likely pathogenic. This study supports the utility of long-read DNA sequencing and complementary RNA approaches to tackle unsolved cases of hereditary disease.

Kinesin-1-powered microtubules have emerged as versatile components in biocomputing and biosensing technologies. However, the inability to identify and track individual microtubules has constrained their applications to ensemble behaviors, limiting their potential for single-entity-based nanotechnologies. To address this challenge, we present a novel method for encoding digital information directly onto individual microtubules using photobleaching patterns. Binary numbers (1 to 15) were encoded within ∼12 μm segments of moving microtubules by photobleaching with a stationary pulsed laser, creating spatial frequency patterns corresponding to distinct bits of information. Fourier analysis enabled the accurate retrieval of the encoded data, demonstrating the feasibility of direct information storage and retrieval on macromolecular structures. This approach offers a transformative solution for recording microtubule trajectories within nanotechnological devices by encoding path information directly onto microtubules at branch points, obviating the need for video-based tracking. We anticipate that this innovation will advance the development of individualized microtubule-based technologies.

Introduction: Peritoneal, pericardial and pleural mesothelioma (PeM/PcM/PM) are rare and aggressive diseases with limited survival. Molecularly guided therapy is currently not part of standard care. Methods: This study integrates molecular and clinical data from 51 patients (among them 28 PM, one PcM, 21 PeM and one synchronous PeM/PM) enrolled in the National Center for Tumor Diseases and the German Cancer Consortium (NCT/DKTK) Molecularly Aided Stratification for Tumor Eradication Research (MASTER), a multicenter precision oncology registry trial addressing adults with rare advanced-stage cancers. Analysis comprised both somatic and germline whole exome sequencing/whole genome sequencing and transcriptome analysis leading to personalized treatment recommendations issued by a dedicated molecular tumor board. To assess clinical efficacy, progression-free survival (PFS) ratios comparing molecularly informed therapies (PFS2) to preceding systemic therapies (PFS1) were calculated. Efficacy of immune checkpoint inhibition applied during the observation period was assessed accordingly. Results: Cancer-related genes altered in more than 5 out of 44 assessable patients were BAP1, CDKN2A, NF2, SETD2 and TP53. Somatic (n = 23) or germline (n = 9) alterations in homologous recombination-related genes were detected in 27/44 patients. In 21/44 cases, they were supported by positive combined homologous recombination deficiency scores or BRCAness signature. Following American College of Medical Genetics and Genomics guidelines, (likely) pathogenic germline variants in autosomal dominant cancer predisposition genes were found in 8/51 patients. Molecular tumor board recommendations were issued in 46 cases and applied in 6 cases. Mean PFS ratio was 2.45 (n = 5). Median PFS2 was 6.5 months (n = 6), median PFS1 was 4.0 months (n = 5). A total of 27 patients received immune checkpoint inhibition during the observation period leading to a mean PFS ratio of 1.69 (n = 19). Conclusions: In mesothelioma, comprehensive molecular analysis can provide valuable clinically actionable information. Molecularly informed therapy recommendations can lead to clinical benefit.