Phase separation is an important mechanism to generate certain biomolecular condensates and organize the cell interior. Condensate formation and function remain incompletely understood due to difficulties in visualizing the condensate interior at high resolution. Here we analyzed the structure of biochemically reconstituted chromatin condensates through cryo-electron tomography. We found that traditional blotting methods of sample preparation were inadequate, and high-pressure freezing plus focused ion beam milling was essential to maintain condensate integrity. To identify densely packed molecules within the condensate, we integrated deep learning-based segmentation with novel context-aware template matching. Our approaches were developed on chromatin condensates, and were also effective on condensed regions of in situ native chromatin. Using these methods, we determined the average structure of nucleosomes to 6.1 and 12 Å resolution in reconstituted and native systems, respectively, and found that nucleosomes have a nearly random orientation distribution in both cases. Our methods should be applicable to diverse biochemically reconstituted biomolecular condensates and to some condensates in cells.

Phase separation is an important mechanism to generate certain biomolecular condensates and organize the cell interior. Condensate formation and function remain incompletely understood due to difficulties in visualizing the condensate interior at high resolution. Here, we analyzed the structure of biochemically reconstituted chromatin condensates through cryoelectron tomography. We found that traditional blotting methods of sample preparation were inadequate, and high-pressure freezing plus focused ion beam milling was essential to maintain condensate integrity. To identify densely packed molecules within the condensate, we integrated deep learning-based segmentation with context-aware template matching. Our approaches were developed on chromatin condensates and were also effective on condensed regions of in situ native chromatin. Using these methods, we determined the average structure of nucleosomes to 6.1 and 12 Å resolution in reconstituted and native systems, respectively, found that nucleosomes form heterogeneous interaction networks in both cases, and gained insight into the molecular origins of surface tension in chromatin condensates. Our methods should be applicable to biomolecular condensates containing large and distinctive components in both biochemical reconstitutions and certain cellular systems.

Preprint: https://www.biorxiv.org/content/10.1101/2024.12.01.626131v2

Genes are regulated by transcription factors that bind to regions of genomic DNA called enhancers. Considerable effort is focused on identifying transcription factor binding sites, with the goal of predicting gene expression from DNA sequence. Despite this effort, general, predictive models of enhancer function are currently lacking. Here we combine quantitative models of enhancer function with manipulations using engineered transcription factors to examine the extent to which enhancer function can be controlled in a quantitatively predictable manner. Our models, which incorporate few free parameters, can accurately predict the contributions of ectopic transcription factor inputs. These models allow the predictable 'tuning' of enhancers, providing a framework for the quantitative control of enhancers with engineered transcription factors.

Recently it was demonstrated that long-lived quantum coherence exists during excitation energy transport in photosynthesis. It is a valid question up to which length, time and mass scales quantum coherence may extend, how one may detect this coherence and what, if any, role it plays in the dynamics of the system. Here we suggest that the selectivity filter of ion channels may exhibit quantum coherence, which might be relevant for the process of ion selectivity and conduction. We show that quantum resonances could provide an alternative approach to ultrafast two-dimensional (2D) spectroscopy to probe these quantum coherences. We demonstrate that the emergence of resonances in the conduction of ion channels that are modulated periodically by time-dependent external electric fields can serve as signatures of quantum coherence in such a system. Assessments of experimental feasibility and specific paths towards the experimental realization of such experiments are presented.

Quantum conditions on the control of dynamics of a system coupled to an environment are obtained. Specifically, consider a system initially in a system subspace H(0) of dimensionality M(0), which evolves to populate system subspaces H(1), H(2) of dimensionalities M(1), M(2). Then, there always exists an initial state in H(0) that does not evolve into H(2) if M(0)>dM(2), where 2

Targeting visually identified neurons for electrophysiological recording is a fundamental neuroscience technique; however, its potential is hampered by poor visualization of pipette tips in deep brain tissue. We describe quantum dot-coated glass pipettes that provide strong two-photon contrast at deeper penetration depths than those achievable with current methods. We demonstrated the pipettes' utility in targeted patch-clamp recording experiments and single-cell electroporation of identified rat and mouse neurons in vitro and in vivo.

In April 2020, the QUality Assessment and REProducibility for Instruments and Images in Light Microscopy (QUAREP-LiMi) initiative was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models, and tools, including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research. This White Paper 1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; 2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of stakeholders including, researchers, imaging scientists, bioimage analysts, bioimage informatics developers, corporate partners, funding agencies, standards organizations, scientific publishers, and observers of such; 3) outlines the current actions of the QUAREP-LiMi initiative, and 4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC. To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data metrics.

When searching sequence databases for RNAs, it is desirable to score both primary sequence and RNA secondary structure similarity. Covariance models (CMs) are probabilistic models well-suited for RNA similarity search applications. However, the computational complexity of CM dynamic programming alignment algorithms has limited their practical application. Here we describe an acceleration method called query-dependent banding (QDB), which uses the probabilistic query CM to precalculate regions of the dynamic programming lattice that have negligible probability, independently of the target database. We have implemented QDB in the freely available Infernal software package. QDB reduces the average case time complexity of CM alignment from LN(2.4) to LN(1.3) for a query RNA of N residues and a target database of L residues, resulting in a 4-fold speedup for typical RNA queries. Combined with other improvements to Infernal, including informative mixture Dirichlet priors on model parameters, benchmarks also show increased sensitivity and specificity resulting from improved parameterization.