Explaining transmission rate variations and forecasting epidemic spread in multiple regions with a semiparametric mixed effects SIR model.

The transmission rate is a central parameter in mathematical models of infectious disease. Its pivotal role in outbreak dynamics makes estimating the current transmission rate and uncovering its dependence on relevant covariates a core challenge in epidemiological research as well as public health policy evaluation. Here, we develop a method for flexibly inferring a time-varying transmission rate parameter, modeled as a function of covariates and a smooth Gaussian process (GP). The transmission rate model is further embedded in a hierarchy to allow information borrowing across parallel streams of regional incidence data. Crucially, the method makes use of optional vaccination data as a first step toward modeling of endemic infectious diseases. Computational techniques borrowed from the Bayesian spatial analysis literature enable fast and reliable posterior computation. Simulation studies reveal that the method recovers true covariate effects at nominal coverage levels. We analyze data from the COVID-19 pandemic and validate forecast intervals on held-out data. User-friendly software is provided to enable practitioners to easily deploy the method in public health research.

Exact limits of inference in coalescent models.

Recovery of population size history from molecular sequence data is an important problem in population genetics. Inference commonly relies on a coalescent model linking the population size history to genealogies. The high computational cost of estimating parameters from these models usually compels researchers to select a subset of the available data or to rely on insufficient summary statistics for statistical inference. We consider the problem of recovering the true population size history from two possible alternatives on the basis of coalescent time data previously considered by Kim et al. (2015). We improve upon previous results by giving exact expressions for the probability of correctly distinguishing between the two hypotheses as a function of the separation between the alternative size histories, the number of individuals, loci, and the sampling times. In more complicated settings we estimate the exact probability of correct recovery by Monte Carlo simulation. Our results give considerably more pessimistic inferential limits than those previously reported. We also extended our analyses to pairwise SMC and SMC' models of recombination. This work is relevant for optimal design when the inference goal is to test scientific hypotheses about population size trajectories in coalescent models with and without recombination.

TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS.

Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. We derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions.

Coordination of microtubule and microfilament dynamics by Drosophila Rho1, Spire and Cappuccino.

The actin-nucleation factors Spire and Cappuccino (Capu) regulate the onset of ooplasmic streaming in Drosophila melanogaster. Although this streaming event is microtubule-based, actin assembly is required for its timing. It is not understood how the interaction of microtubules and microfilaments is mediated in this context. Here, we demonstrate that Capu and Spire have microtubule and microfilament crosslinking activity. The spire locus encodes several distinct protein isoforms (SpireA, SpireC and SpireD). SpireD was recently shown to nucleate actin, but the activity of the other isoforms has not been addressed. We find that SpireD does not have crosslinking activity, whereas SpireC is a potent crosslinker. We show that SpireD binds to Capu and inhibits F-actin/microtubule crosslinking, and activated Rho1 abolishes this inhibition, establishing a mechanistic basis for the regulation of Capu and Spire activity. We propose that Rho1, cappuccino and spire are elements of a conserved developmental cassette that is capable of directly mediating crosstalk between microtubules and microfilaments.

Anti-inflammatory actions of lipoxin A4 and aspirin-triggered lipoxin are SOCS-2 dependent.

Control of inflammation is crucial to prevent damage to the host during infection. Lipoxins and aspirin-triggered lipoxins are crucial modulators of proinflammatory responses; however, their intracellular mechanisms have not been completely elucidated. We previously showed that lipoxin A4 (LXA4) controls migration of dendritic cells (DCs) and production of interleukin (IL)-12 in vivo. In the absence of LXA4 biosynthetic pathways, the resulting uncontrolled inflammation during infection is lethal, despite pathogen clearance. Here we show that lipoxins activate two receptors in DCs, AhR and LXAR, and that this activation triggers expression of suppressor of cytokine signaling (SOCS)-2. SOCS-2-deficient DCs are hyper-responsive to microbial stimuli, as well as refractory to the inhibitory actions of LXA4, but not to IL-10. Upon infection with an intracellular pathogen, SOCS-2-deficient mice had uncontrolled production of proinflammatory cytokines, decreased microbial proliferation, aberrant leukocyte infiltration and elevated mortality. We also show that SOCS-2 is a crucial intracellular mediator of the anti-inflammatory actions of aspirin-induced lipoxins in vivo.

Removing the influence of group variables in high-dimensional predictive modelling.

In many application areas, predictive models are used to support or make important decisions. There is increasing awareness that these models may contain spurious or otherwise undesirable correlations. Such correlations may arise from a variety of sources, including batch effects, systematic measurement errors, or sampling bias. Without explicit adjustment, machine learning algorithms trained using these data can produce poor out-of-sample predictions which propagate these undesirable correlations. We propose a method to pre-process the training data, producing an adjusted dataset that is statistically independent of the nuisance variables with minimum information loss. We develop a conceptually simple approach for creating an adjusted dataset in high-dimensional settings based on a constrained form of matrix decomposition. The resulting dataset can then be used in any predictive algorithm with the guarantee that predictions will be statistically independent of the group variable. We develop a scalable algorithm for implementing the method, along with theory support in the form of independence guarantees and optimality. The method is illustrated on some simulation examples and applied to two case studies: removing machine-specific correlations from brain scan data, and removing race and ethnicity information from a dataset used to predict recidivism. That the motivation for removing undesirable correlations is quite different in the two applications illustrates the broad applicability of our approach.

Sisyphus, the Drosophila myosin XV homolog, traffics within filopodia transporting key sensory and adhesion cargos.

Unconventional myosin proteins of the MyTH-FERM superclass are involved in intrafilopodial trafficking, are thought to be mediators of membrane-cytoskeleton interactions, and are linked to several forms of deafness in mammals. Here we show that the Drosophila myosin XV homolog, Sisyphus, is expressed at high levels in leading edge cells and their cellular protrusions during the morphogenetic process of dorsal closure. Sisyphus is required for the correct alignment of cells on opposing sides of the fusing epithelial sheets, as well as for adhesion of the cells during the final zippering/fusion phase. We have identified several putative Sisyphus cargos, including DE-cadherin (also known as Shotgun) and the microtubule-linked proteins Katanin-60, EB1, Milton and aPKC. These cargos bind to the Sisyphus FERM domain, and their binding is in some cases mutually exclusive. Our data suggest a mechanism for Sisyphus in which it maintains a balance between actin and microtubule cytoskeleton components, thereby contributing to cytoskeletal cross-talk necessary for regulating filopodial dynamics during dorsal closure.

The Type I IFN response to infection with Mycobacterium tuberculosis requires ESX-1-mediated secretion and contributes to pathogenesis.

The ESX-1 secretion system is a major determinant of Mycobacterium tuberculosis virulence, although the pathogenic mechanisms resulting from ESX-1-mediated transport remain unclear. By global transcriptional profiling of tissues from mice infected with either wild-type or ESX-1 mutant bacilli, we found that host genes controlled by ESX-1 in vivo are predominantly IFN regulated. ESX-1-mediated secretion is required for the production of host type I IFNs during infection in vivo and in macrophages in vitro. The macrophage signaling pathway leading to the production of type I IFN required the host kinase TANK-binding kinase 1 and occurs independently of TLR signaling. Importantly, the induction of type I IFNs during M. tuberculosis infection is a pathogenic mechanism as mice lacking the type I IFNR were more restrictive for bacterial growth in the spleen than wild-type mice, although growth in the lung was unaffected. We propose that the ESX-1 secretion system secretes effectors into the cytosol of infected macrophages, thereby triggering the type I IFN response for the manipulation of host immunity.

Drosophila Rho-kinase (DRok) is required for tissue morphogenesis in diverse compartments of the egg chamber during oogenesis.

The Rho-kinases are widely utilized downstream targets of the activated Rho GTPase that have been directly implicated in many aspects of Rho-dependent effects on F-actin assembly, acto-myosin contractility, and microtubule stability, and consequently play an essential role in regulating cell shape, migration, polarity, and division. We have determined that the single closely related Drosophila Rho-kinase ortholog, DRok, is required for several aspects of oogenesis, including maintaining the integrity of the oocyte cortex, actin-mediated tethering of nurse cell nuclei, "dumping" of nurse cell contents into the oocyte, establishment of oocyte polarity, and the trafficking of oocyte yolk granules. These defects are associated with abnormalities in DRok-dependent actin dynamics and appear to be mediated by multiple downstream effectors of activated DRok that have previously been implicated in oogenesis. DRok regulates at least one of these targets, the membrane cytoskeletal cross-linker DMoesin, via a direct phosphorylation that is required to promote localization of DMoesin to the oocyte cortex. The collective oogenesis defects associated with DRok deficiency reveal its essential role in multiple aspects of proper oocyte formation and suggest that DRok defines a novel class of oogenesis determinants that function as key regulators of several distinct actin-dependent processes required for proper tissue morphogenesis.

Allele-specific inhibitors of protein tyrosine phosphatases.

Protein tyrosine phosphatases (PTPs) are critical cell-signaling molecules. Inhibitors that are selective for individual PTPs would be valuable tools for dissecting complicated phosphorylation networks. However, the common architecture of PTP active sites impedes the discovery of such compounds. To achieve target selectivity, we have redesigned a PTP/inhibitor interface. Site-directed mutagenesis of a prototypical phosphatase, PTP1B, was used to generate "inhibitor-sensitized" PTPs. The PTP1B mutants were targeted by modifying a broad specificity PTP inhibitor with chemical groups that are sterically incompatible with wild-type PTP active sites. From a small panel of putative inhibitors, compounds that selectively inhibit Ile219Ala PTP1B over the wild-type enzyme were identified. Importantly, the corresponding mutation also conferred novel inhibitor sensitivity to T-cell PTP, suggesting that a readily identifiable point mutation can be used to generate a variety of inhibitor-sensitive PTPs.

Rho GTPase function in flies: insights from a developmental and organismal perspective.

Morphogenesis is a key event in the development of a multicellular organism and is reliant on coordinated transcriptional and signal transduction events. To establish the segmented body plan that underlies much of metazoan development, individual cells and groups of cells must respond to exogenous signals with complex movements and shape changes. One class of proteins that plays a pivotal role in the interpretation of extracellular cues into cellular behavior is the Rho family of small GTPases. These molecular switches are essential components of a growing number of signaling pathways, many of which regulate actin cytoskeletal remodeling. Much of our understanding of Rho biology has come from work done in cell culture. More recently, the fruit fly Drosophila melanogaster has emerged as an excellent genetic system for the study of these proteins in a developmental and organismal context. Studies in flies have greatly enhanced our understanding of pathways involving Rho GTPases and their roles in development.