Correction: The impact of ribosomal interference, codon usage, and exit tunnel interactions on translation elongation rate variation.

[This corrects the article DOI: 10.1371/journal.pgen.1007166.].

OPERATOR NORM INEQUALITIES BETWEEN TENSOR UNFOLDINGS ON THE PARTITION LATTICE.

Interest in higher-order tensors has recently surged in data-intensive fields, with a wide range of applications including image processing, blind source separation, community detection, and feature extraction. A common paradigm in tensor-related algorithms advocates unfolding (or flattening) the tensor into a matrix and applying classical methods developed for matrices. Despite the popularity of such techniques, how the functional properties of a tensor changes upon unfolding is currently not well understood. In contrast to the body of existing work which has focused almost exclusively on matricizations, we here consider all possible unfoldings of an order-k tensor, which are in one-to-one correspondence with the set of partitions of {1, …, k}. We derive general inequalities between the lp -norms of arbitrary unfoldings defined on the partition lattice. In particular, we demonstrate how the spectral norm (p = 2) of a tensor is bounded by that of its unfoldings, and obtain an improved upper bound on the ratio of the Frobenius norm to the spectral norm of an arbitrary tensor. For specially-structured tensors satisfying a generalized definition of orthogonal decomposability, we prove that the spectral norm remains invariant under specific subsets of unfolding operations.

Glycogen synthase kinase 3 inhibition controls Mycobacterium tuberculosis infection.

Compounds targeting host control of infectious diseases provide an attractive alternative to antimicrobials. A phenotypic screen of a kinase library identified compounds targeting glycogen synthase kinase 3 as potent inhibitors of Mycobacterium tuberculosis (Mtb) intracellular growth in the human THP-1 cell line and primary human monocytes-derived macrophages (hMDM). CRISPR knockouts and siRNA silencing showed that GSK3 isoforms are needed for the growth of Mtb and that a selected compound, P-4423632 targets GSK3ß. GSK3 inhibition was associated with macrophage apoptosis governed by the Mtb secreted protein tyrosine phosphatase A (PtpA). Phospho-proteome analysis of macrophages response to infection revealed a wide array of host signaling and apoptosis pathways controlled by GSK3 and targeted by P-4423632. P-4423632 was additionally found to be active against other intracellular pathogens. Our findings strengthen the notion that targeting host signaling to promote the infected cell's innate antimicrobial capacity is a feasible and attractive host-directed therapy approach.

AlignOT: An Optimal Transport Based Algorithm for Fast 3D Alignment With Applications to Cryogenic Electron Microscopy Density Maps.

Aligning electron density maps from Cryogenic electron microscopy (cryo-EM) is a first key step for studying multiple conformations of a biomolecule. As this step remains costly and challenging, with standard alignment tools being potentially stuck in local minima, we propose here a new procedure, called AlignOT, which relies on the use of computational optimal transport (OT) to align EM maps in 3D space. By embedding a fast estimation of OT maps within a stochastic gradient descent algorithm, our method searches for a rotation that minimizes the Wasserstein distance between two maps, represented as point clouds. We quantify the impact of various parameters on the precision and accuracy of the alignment, and show that AlignOT can outperform the standard local alignment methods, with an increased range of rotation angles leading to proper alignment. We further benchmark AlignOT on various pairs of experimental maps, which account for different types of conformational heterogeneities and geometric properties. As our experiments show good performance, we anticipate that our method can be broadly applied to align 3D EM maps.

Defining an action of SO(d)-rotations on images generated by projections of d-dimensional objects: Applications to pose inference with Geometric VAEs.

Recent advances in variational autoencoders (VAEs) have enabled learning latent manifolds as compact Lie groups, such as SO(d). Since this approach assumes that data lies on a subspace that is homeomorphic to the Lie group itself, we here investigate how this assumption holds in the context of images that are generated by projecting a d-dimensional volume with unknown pose in SO(d). Upon examining different theoretical candidates for the group and image space, we show that the attempt to define a group action on the data space generally fails, as it requires more specific geometric constraints on the volume. Using geometric VAEs, our experiments confirm that this constraint is key to proper pose inference, and we discuss the potential of these results for applications and future work.

Les récents progrès dans le domaine des autoencodeurs variationnels (VAEs) ont permis l'apprentissage de variétés latentes sur des groupes de Lie compacts, tels que SO(d). Une telle approche supposant l'espace des données homéomorphe au groupe de Lie, nous étudions ici la validité de cette hypothèse dans le contexte d'images générées par projection d'un volume de dimension d, dont la pose dans SO(d) est inconnue. Après examen de différents candidats définissant l'espace des images et groupe, on montre que l'on ne peut de manière générale obtenir une action de groupe, sans une contrainte supplémentaire sur le volume. En appliquant des VAEs géométriques, nos expériences confirment que ces contraintes géométriques sont essentielles pour l'inférence de la pose associée au volume projeté, et nous discutons pour conclure des applications potentielles de ces résultats.

Analysis of Ribosome Profiling Data.

Ribosome profiling methods are based on high-throughput sequencing of ribosome-protected mRNA footprints and allow to study in detail translational changes. Bioinformatic and statistical tools are necessary to analyze sequencing data. Here, we describe our developed methods for a fast and reliable quality control of ribosome profiling data, to efficiently visualize ribosome positions and to estimate ribosome speed in an unbiased way. The methodology described here is applicable to several genetic and environmental conditions including stress and are based on the R package RiboVIEW and calculation of quantitative estimates of local and global translation speed, based on a biophysical model of translation dynamics.

Application of transport-based metric for continuous interpolation between cryo-EM density maps.

Cryogenic electron microscopy (cryo-EM) has become widely used for the past few years in structural biology, to collect single images of macromolecules "frozen in time". As this technique facilitates the identification of multiple conformational states adopted by the same molecule, a direct product of it is a set of 3D volumes, also called EM maps. To gain more insights on the possible mechanisms that govern transitions between different states, and hence the mode of action of a molecule, we recently introduced a bioinformatic tool that interpolates and generates morphing trajectories joining two given EM maps. This tool is based on recent advances made in optimal transport, that allow efficient evaluation of Wasserstein barycenters of 3D shapes. As the overall performance of the method depends on various key parameters, including the sensitivity of the regularization parameter, we performed various numerical experiments to demonstrate how MorphOT can be applied in different contexts and settings. Finally, we discuss current limitations and further potential connections between other optimal transport theories and the conformational heterogeneity problem inherent with cryo-EM data.

The length of the shortest telomere as the major determinant of the onset of replicative senescence.

The absence of telomerase in many eukaryotes leads to the gradual shortening of telomeres, causing replicative senescence. In humans, this proliferation barrier constitutes a tumor suppressor mechanism and may be involved in cellular aging. Yet the heterogeneity of the senescence phenotype has hindered the understanding of its onset. Here we investigated the regulation of telomere length and its control of senescence heterogeneity. Because the length of the shortest telomeres can potentially regulate cell fate, we focus on their dynamics in Saccharomyces cerevisiae. We developed a stochastic model of telomere dynamics built on the protein-counting model, where an increasing number of protein-bound telomeric repeats shift telomeres into a nonextendable state by telomerase. Using numerical simulations, we found that the length of the shortest telomere is well separated from the length of the others, suggesting a prominent role in triggering senescence. We evaluated this possibility using classical genetic analyses of tetrads, combined with a quantitative and sensitive assay for senescence. In contrast to mitosis of telomerase-negative cells, which produces two cells with identical senescence onset, meiosis is able to segregate a determinant of senescence onset among the telomerase-negative spores. The frequency of such segregation is in accordance with this determinant being the length of the shortest telomere. Taken together, our results substantiate the length of the shortest telomere as being the key genetic marker determining senescence onset in S. cerevisiae.