Publikationen

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.

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.

Biomolecular condensates are thought to create subcellular microenvironments that regulate specific biochemical activities. Extensive in vitro work has helped link condensate formation to a wide range of cellular processes, including gene expression, nuclear transport, signalling and stress responses. However, testing the relationship between condensate formation and function in cells is more challenging. In particular, the extent to which the cellular functions of condensates depend on the nature of the molecular interactions through which the condensates form is a major outstanding question. Here, we review results from recent genetic complementation experiments in cells, and highlight how genetic complementation provides important insights into cellular functions and functional specificity of biomolecular condensates. Combined with observations from human genetic disease, these experiments suggest that diverse condensate-promoting regions within cellular proteins confer different condensate compositions, biophysical properties and functions.

Increasing insights into how sequence motifs in intrinsically disordered regions (IDRs) provide functions underscore the need for systematic motif detection. Contrary to structured regions where motifs can be readily identified from sequence alignments, the rapid evolution of IDRs limits the usage of alignment-based tools in reliably detecting motifs within. Here, we developed SHARK-capture, an alignment-free motif detection tool designed for difficult-to-align regions. SHARK-capture innovates on word-based methods by flexibly incorporating amino acid physicochemistry to assess motif similarity without requiring rigid definitions of equivalency groups. SHARK-capture offers consistently strong performance in a systematic benchmark, with superior residue-level performance. SHARK-capture identified known functional motifs across orthologs of the microtubule-associated zinc finger protein BuGZ. We also identified a short motif in the IDR of S. cerevisiae RNA helicase Ded1p, which we experimentally verified to be capable of promoting ATPase activity. Our improved performance allows us to systematically calculate 10,889 motifs for 2695 yeast IDRs and provide it as a resource. SHARK-capture offers the most precise tool yet for the systematic identification of conserved regions in IDRs and is freely available as a Python package (https://pypi.org/project/bio-shark/) and on https://git.mpi-cbg.de/tothpetroczylab/shark.

The green alga Chlamydomonas is an important and versatile model organism for research topics ranging from photosynthesis and metabolism, cilia, and basal bodies to cellular communication and the cellular cycle and is of significant interest for green bioengineering processes. The genome in this unicellular green alga is contained in 17 haploid chromosomes and codes for 16 883 protein coding genes. Functional genomics, as well as biotechnological applications, rely on the ability to remove, add, and change these genes in a controlled and efficient manner. In this review, the history of gene editing in Chlamydomonas is put in the context of the wider developments in genetics to demonstrate how many of the key developments to engineer these algae follow the global trends and the availability of technology. Building on this background, an overview of the state of the art in Chlamydomonas engineering is given, focusing primarily on the practical aspects while giving examples of recent applications. Commonly encountered Chlamydomonas-specific challenges, recent developments, and community resources are presented, and finally, a comprehensive discussion on the emergence and evolution of CRISPR/Cas-based precision gene editing is given. An outline of possible future paths for gene editing based on current global trends in genetic engineering and tools for gene editing is presented.

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.

Aptamers, nucleic acid ligands targeting specific molecules, have emerged as drug candidates, sensors, imaging tools and nanotechnology building blocks. The predominant method for their discovery, systematic evolution of ligands by exponential enrichment, while successful, is laborious, time-consuming and often results in candidates enriched for unintended criteria. Here we present UltraSelex, a noniterative method that combines biochemical partitioning, high-throughput sequencing and computational signal-to-background rank modeling for discovering RNA aptamers in about 1 day. UltraSelex identified high-affinity RNA aptamers capable of binding a fluorogenic silicon rhodamine dye and two protein targets, the SARS-CoV-2 RNA-dependent RNA polymerase and HIV reverse transcriptase, enabling live-cell RNA imaging and efficient enzyme inhibition, respectively. From the ranked sequences, minimal aptamer motifs could be easily inferred. UltraSelex provides a rapid route to reveal new drug candidates and diagnostic tools.