Rhythmidia: A modern tool for circadian period analysis of filamentous fungi.

Circadian rhythms are ubiquitous across the kingdoms of life and serve important roles in regulating physiology and behavior at many levels. These rhythms occur in ~24-hour cycles and are driven by a core molecular oscillator. Circadian timekeeping enables organisms to anticipate daily changes by timing their growth and internal processes. Neurospora crassa is a model organism with a long history in circadian biology, having conserved eukaryotic clock properties and observable circadian phenotypes. A core approach for measuring circadian function in Neurospora is to follow daily oscillations in the direction of growth and spore formation along a thin glass tube (race tube). While leveraging robust phenotypic readouts is useful, interpreting the outputs of large-scale race tube experiments by hand can be time-consuming and prone to human error. To provide the field with an efficient tool for analyzing race tubes, we present Rhythmidia, a graphical user interface (GUI) tool written in Python for calculating circadian periods and growth rates of Neurospora. Rhythmidia is open source, has been benchmarked against the current state-of-the-art, and is easily accessible on GitHub.

In-Cell Association of a Bioorthogonal Tubulin.

Studies of proteins from one organism in another organism's cells have shown that such exogenous proteins stick more, pointing toward coevolution of the cytoplasm and protein surface to minimize stickiness. Here we flip this question around by asking whether exogenous proteins can assemble efficiently into their target complexes in a non-native cytoplasm. We use as our model system the assembly of BtubA and BtubB from Prosthecobacter hosted in human U-2 OS cells. BtubA and B evolved from eukaryotic tubulins after horizontal gene transfer, but they have low surface sequence identity with the homologous human tubulins and do not respond to tubulin drugs such as nocodazole. In U-2 OS cells, BtubA and B assemble efficiently into dimers compared to in vitro, and the wild-type BtubA and B proteins subsequently are able to form microtubules as well. We find that generic crowding effects (Ficoll 70 in vitro) contribute significantly to efficient dimer assembly when compared to sticking interactions (U-2 OS cell lysate in vitro), consistent with the notion that a generic mechanism such as crowding can be effective at driving assembly of exogenous proteins, even when protein-cytoplasm quinary structure and sticking have been modified in a non-native cytoplasm. A simple Monte Carlo model of in vitro and in-cell interactions, treating BtubA and B as sticky dipoles in a matrix of sticky or nonsticky crowders, rationalizes all the experimental trends with two adjustable parameters and reveals nucleation as the likely mechanism for the time-scale separation between dimer- and tubule formation in-cell and in vitro.

SOURSOP: A Python Package for the Analysis of Simulations of Intrinsically Disordered Proteins.

Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite simulation analysis of unfolded regions of proteins (SOURSOP), an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.

SOURSOP: A Python package for the analysis of simulations of intrinsically disordered proteins.

Conformational heterogeneity is a defining hallmark of intrinsically disordered proteins and protein regions (IDRs). The functions of IDRs and the emergent cellular phenotypes they control are associated with sequence-specific conformational ensembles. Simulations of conformational ensembles that are based on atomistic and coarse-grained models are routinely used to uncover the sequence-specific interactions that may contribute to IDR functions. These simulations are performed either independently or in conjunction with data from experiments. Functionally relevant features of IDRs can span a range of length scales. Extracting these features requires analysis routines that quantify a range of properties. Here, we describe a new analysis suite SOURSOP, an object-oriented and open-source toolkit designed for the analysis of simulated conformational ensembles of IDRs. SOURSOP implements several analysis routines motivated by principles in polymer physics, offering a unique collection of simple-to-use functions to characterize IDR ensembles. As an extendable framework, SOURSOP supports the development and implementation of new analysis routines that can be easily packaged and shared.