Shootin-1 is required for nervous system development in zebrafish.

BACKGROUND: Semaphorin6A (Sema6A) and its PlexinA2 (PlxnA2) receptor canonically function as repulsive axon guidance cues. To understand downstream signaling mechanisms, we performed a microarray screen and identified the "clutch molecule" shootin-1 (shtn-1) as a transcriptionally repressed target. Shtn-1 is a key proponent of cell migration and neuronal polarization and must be regulated during nervous system development. The mechanisms of Shtn-1 regulation and the phenotypic consequences of loss of repression are poorly understood. RESULTS: We demonstrate shtn-1 overexpression results in impaired migration of the optic vesicles, lack of retinal pigmented epithelium, and pathfinding errors of retinotectal projections. We also observed patterning defects in the peripheral nervous system. Importantly, these phenotypes were rescued by overexpressing PlxnA2. CONCLUSIONS: We demonstrate a functional role for repression of shtn-1 by PlxnA2 in development of the eyes and peripheral nervous system in zebrafish. These results demonstrate that careful regulation of shtn-1 is critical for development of the nervous system.

Marginal likelihood estimation of negative binomial parameters with applications to RNA-seq data.

RNA-Seq data characteristically exhibits large variances, which need to be appropriately accounted for in any proposed model. We first explore the effects of this variability on the maximum likelihood estimator (MLE) of the dispersion parameter of the negative binomial distribution, and propose instead to use an estimator obtained via maximization of the marginal likelihood in a conjugate Bayesian framework. We show, via simulation studies, that the marginal MLE can better control this variation and produce a more stable and reliable estimator. We then formulate a conjugate Bayesian hierarchical model, and use this new estimator to propose a Bayesian hypothesis test to detect differentially expressed genes in RNA-Seq data. We use numerical studies to show that our much simpler approach is competitive with other negative binomial based procedures, and we use a real data set to illustrate the implementation and flexibility of the procedure.

Identification of target genes downstream of semaphorin6A/PlexinA2 signaling in zebrafish.

BACKGROUND: Semaphorin (Sema)/Plexin (Plxn) signaling is important for many aspects of neuronal development, however, the transcriptional regulation imposed by this signaling pathway is unknown. Previously, we identified an essential role for Sema6A/PlxnA2 signaling in regulating proliferation and cohesion of retinal precursor cells (RPCs) during early eye development. This study used RNA isolated from control, Sema6A-deficient and PlxnA2-deficient zebrafish embryos in a microarray analysis to identify genes that were differentially expressed when this signaling pathway was disrupted. RESULTS: We uncovered a set of 58 transcripts, and all but 1 were up-regulated in both sema6A and plxnA2 morphants. We validated gene expression changes in subset of candidates that are suggested to be involved in proliferation, migration or neuronal positioning. We further functionally evaluated one gene, rasl11b, as contributing to disrupted proliferation in sema6A and plxna2 morphants. Our results suggest rasl11b negatively regulates proliferation of RPCs in the developing zebrafish eye. CONCLUSIONS: Microarray analysis has generated a resource of target genes downstream of Sema6A/PlxnA2 signaling, which can be further investigated to elucidate the downstream effects of this well-studied neuronal and vascular guidance signaling pathway. Developmental Dynamics 246:539-549, 2017. © 2017 Wiley Periodicals, Inc.

Deciphering the Function of New Gonococcal Vaccine Antigens Using Phenotypic Microarrays.

The function and extracellular location of cell envelope proteins make them attractive candidates for developing vaccines against bacterial diseases, including challenging drug-resistant pathogens, such as Neisseria gonorrhoeae A proteomics-driven reverse vaccinology approach has delivered multiple gonorrhea vaccine candidates; however, the biological functions of many of them remain to be elucidated. Herein, the functions of six gonorrhea vaccine candidates-NGO2121, NGO1985, NGO2054, NGO2111, NGO1205, and NGO1344-in cell envelope homeostasis were probed using phenotype microarrays under 1,056 conditions and a ΔbamE mutant (Δngo1780) as a reference of perturbed outer membrane integrity. Optimal growth conditions for an N. gonorrhoeae phenotype microarray assay in defined liquid medium were developed, which can be useful in other applications, including rapid and thorough antimicrobial susceptibility assessment. Our studies revealed 91 conditions having uniquely positive or negative effects on one of the examined mutants. A cluster analysis of 37 and 57 commonly beneficial and detrimental compounds, respectively, revealed three separate phenotype groups: NGO2121 and NGO1985; NGO1344 and BamE; and the trio of NGO1205, NGO2111, and NGO2054, with the last protein forming an independent branch of this cluster. Similar phenotypes were associated with loss of these vaccine candidates in the highly antibiotic-resistant WHO X strain. Based on their extensive sensitivity phenomes, NGO1985 and NGO2121 appear to be the most promising vaccine candidates. This study establishes the principle that phenotype microarrays can be successfully applied to a fastidious bacterial organism, such as N. gonorrhoeae IMPORTANCE Innovative approaches are required to develop vaccines against prevalent and neglected sexually transmitted infections, such as gonorrhea. Herein, we have utilized phenotype microarrays in the first such investigation into Neisseria gonorrhoeae to probe the function of proteome-derived vaccine candidates in cell envelope homeostasis. Information gained from this screening can feed the vaccine candidate decision tree by providing insights into the roles these proteins play in membrane permeability, integrity, and overall N. gonorrhoeae physiology. The optimized screening protocol can be applied in investigations into the function of other hypothetical proteins of N. gonorrhoeae discovered in the expanding number of whole-genome sequences, in addition to revealing phenotypic differences between clinical and laboratory strains.

The type II secretion pathway in Vibrio cholerae is characterized by growth phase-dependent expression of exoprotein genes and is positively regulated by σE.

Vibrio cholerae, an etiological agent of cholera, circulates between aquatic reservoirs and the human gastrointestinal tract. The type II secretion (T2S) system plays a pivotal role in both stages of the lifestyle by exporting multiple proteins, including cholera toxin. Here, we studied the kinetics of expression of genes encoding the T2S system and its cargo proteins. We have found that under laboratory growth conditions, the T2S complex was continuously expressed throughout V. cholerae growth, whereas there was growth phase-dependent transcriptional activity of genes encoding different cargo proteins. Moreover, exposure of V. cholerae to different environmental cues encountered by the bacterium in its life cycle induced transcriptional expression of T2S. Subsequent screening of a V. cholerae genomic library suggested that σ(E) stress response, phosphate metabolism, and the second messenger 3',5'-cyclic diguanylic acid (c-di-GMP) are involved in regulating transcriptional expression of T2S. Focusing on σ(E), we discovered that the upstream region of the T2S operon possesses both the consensus σ(E) and σ(70) signatures, and deletion of the σ(E) binding sequence prevented transcriptional activation of T2S by RpoE. Ectopic overexpression of σ(E) stimulated transcription of T2S in wild-type and isogenic ΔrpoE strains of V. cholerae, providing additional support for the idea that the T2S complex belongs to the σ(E) regulon. Together, our results suggest that the T2S pathway is characterized by the growth phase-dependent expression of genes encoding cargo proteins and requires a multifactorial regulatory network to ensure appropriate kinetics of the secretory traffic and the fitness of V. cholerae in different ecological niches.

An evaluation of inferential procedures for adaptive clinical trial designs with pre-specified rules for modifying the sample size.

Many papers have introduced adaptive clinical trial methods that allow modifications to the sample size based on interim estimates of treatment effect. There has been extensive commentary on type I error control and efficiency considerations, but little research on estimation after an adaptive hypothesis test. We evaluate the reliability and precision of different inferential procedures in the presence of an adaptive design with pre-specified rules for modifying the sampling plan. We extend group sequential orderings of the outcome space based on the stage at stopping, likelihood ratio statistic, and sample mean to the adaptive setting in order to compute median-unbiased point estimates, exact confidence intervals, and P-values uniformly distributed under the null hypothesis. The likelihood ratio ordering is found to average shorter confidence intervals and produce higher probabilities of P-values below important thresholds than alternative approaches. The bias adjusted mean demonstrates the lowest mean squared error among candidate point estimates. A conditional error-based approach in the literature has the benefit of being the only method that accommodates unplanned adaptations. We compare the performance of this and other methods in order to quantify the cost of failing to plan ahead in settings where adaptations could realistically be pre-specified at the design stage. We find the cost to be meaningful for all designs and treatment effects considered, and to be substantial for designs frequently proposed in the literature.

Higher order asymptotics for negative binomial regression inferences from RNA-sequencing data.

RNA sequencing (RNA-Seq) is the current method of choice for characterizing transcriptomes and quantifying gene expression changes. This next generation sequencing-based method provides unprecedented depth and resolution. The negative binomial (NB) probability distribution has been shown to be a useful model for frequencies of mapped RNA-Seq reads and consequently provides a basis for statistical analysis of gene expression. Negative binomial exact tests are available for two-group comparisons but do not extend to negative binomial regression analysis, which is important for examining gene expression as a function of explanatory variables and for adjusted group comparisons accounting for other factors. We address the adequacy of available large-sample tests for the small sample sizes typically available from RNA-Seq studies and consider a higher-order asymptotic (HOA) adjustment to likelihood ratio tests. We demonstrate that 1) the HOA-adjusted likelihood ratio test is practically indistinguishable from the exact test in situations where the exact test is available, 2) the type I error of the HOA test matches the nominal specification in regression settings we examined via simulation, and 3) the power of the likelihood ratio test does not appear to be affected by the HOA adjustment. This work helps clarify the accuracy of the unadjusted likelihood ratio test and the degree of improvement available with the HOA adjustment. Furthermore, the HOA test may be preferable even when the exact test is available because it does not require ad hoc library size adjustments.

Adaptive clinical trial designs with pre-specified rules for modifying the sample size: understanding efficient types of adaptation.

Adaptive clinical trial design has been proposed as a promising new approach that may improve the drug discovery process. Proponents of adaptive sample size re-estimation promote its ability to avoid 'up-front' commitment of resources, better address the complicated decisions faced by data monitoring committees, and minimize accrual to studies having delayed ascertainment of outcomes. We investigate aspects of adaptation rules, such as timing of the adaptation analysis and magnitude of sample size adjustment, that lead to greater or lesser statistical efficiency. Owing in part to the recent Food and Drug Administration guidance that promotes the use of pre-specified sampling plans, we evaluate alternative approaches in the context of well-defined, pre-specified adaptation. We quantify the relative costs and benefits of fixed sample, group sequential, and pre-specified adaptive designs with respect to standard operating characteristics such as type I error, maximal sample size, power, and expected sample size under a range of alternatives. Our results build on others' prior research by demonstrating in realistic settings that simple and easily implemented pre-specified adaptive designs provide only very small efficiency gains over group sequential designs with the same number of analyses. In addition, we describe optimal rules for modifying the sample size, providing efficient adaptation boundaries on a variety of scales for the interim test statistic for adaptation analyses occurring at several different stages of the trial. We thus provide insight into what are good and bad choices of adaptive sampling plans when the added flexibility of adaptive designs is desired.

Imperfect gold standards for biomarker evaluation.

BACKGROUND: Serum creatinine has been used as the diagnostic test for acute kidney injury (AKI) for decades despite having imperfect sensitivity and specificity. Novel tubular injury biomarkers may revolutionize the diagnosis of AKI; however, even if a novel tubular injury biomarker is 100% sensitive and 100% specific, it may appear inaccurate when using serum creatinine as the gold standard. CONCLUSIONS: In general, the apparent diagnostic performance of a biomarker depends not only on its ability to detect injury but also on disease prevalence and the sensitivity and specificity of the imperfect gold standard. Apparent errors in diagnosis using a new biomarker may be a reflection of errors in the imperfect gold standard itself rather than poor performance of the biomarker.

Imperfect gold standards for kidney injury biomarker evaluation.

Clinicians have used serum creatinine in diagnostic testing for acute kidney injury for decades, despite its imperfect sensitivity and specificity. Novel tubular injury biomarkers may revolutionize the diagnosis of acute kidney injury; however, even if a novel tubular injury biomarker is 100% sensitive and 100% specific, it may appear inaccurate when using serum creatinine as the gold standard. Acute kidney injury, as defined by serum creatinine, may not reflect tubular injury, and the absence of changes in serum creatinine does not assure the absence of tubular injury. In general, the apparent diagnostic performance of a biomarker depends not only on its ability to detect injury, but also on disease prevalence and the sensitivity and specificity of the imperfect gold standard. Assuming that, at a certain cutoff value, serum creatinine is 80% sensitive and 90% specific and disease prevalence is 10%, a new perfect biomarker with a true 100% sensitivity may seem to have only 47% sensitivity compared with serum creatinine as the gold standard. Minimizing misclassification by using more strict criteria to diagnose acute kidney injury will reduce the error when evaluating the performance of a biomarker under investigation. Apparent diagnostic errors using a new biomarker may be a reflection of errors in the imperfect gold standard itself, rather than poor performance of the biomarker. The results of this study suggest that small changes in serum creatinine alone should not be used to define acute kidney injury in biomarker or interventional studies.

Fall Risk Prediction in Older Adults Using Free-Text Nursing Notes and Medications in Electronic Health Records.

Nursing notes in Electronic Health Records (EHR) contain critical health information, including fall risk factors. However, an exploration of fall risk prediction using nursing notes is not well examined. In this study, we explored deep learning architectures to predict fall risk in older adults using text in nursing notes and medications in the EHR. EHR predictor data and fall events outcome data were obtained from 162 older adults living at TigerPlace, a senior living facility located in Columbia, MO. We used pre-trained BioWordVec embeddings to represent the words in the clinical notes and medications and trained multiple recurrent neural network-based natural language processing models to predict future fall events. Our final model predicted falls with an accuracy of 0.81, a sensitivity of 0.75, a specificity of 0.83, and an F1 score of 0.82. This preliminary exploratory analysis provides supporting evidence that fall risk can be predicted from clinical notes and medications. Future studies will utilize additional data modalities available in the EHR to potentially improve fall risk prediction from EHR data.

Exploring the benefits of adaptive sequential designs in time-to-event endpoint settings.

Sequential analysis is frequently employed to address ethical and financial issues in clinical trials. Sequential analysis may be performed using standard group sequential designs, or, more recently, with adaptive designs that use estimates of treatment effect to modify the maximal statistical information to be collected. In the general setting in which statistical information and clinical trial costs are functions of the number of subjects used, it has yet to be established whether there is any major efficiency advantage to adaptive designs over traditional group sequential designs. In survival analysis, however, statistical information (and hence efficiency) is most closely related to the observed number of events, while trial costs still depend on the number of patients accrued. As the number of subjects may dominate the cost of a trial, an adaptive design that specifies a reduced maximal possible sample size when an extreme treatment effect has been observed may allow early termination of accrual and therefore a more cost-efficient trial. We investigate and compare the tradeoffs between efficiency (as measured by average number of observed events required), power, and cost (a function of the number of subjects accrued and length of observation) for standard group sequential methods and an adaptive design that allows for early termination of accrual. We find that when certain trial design parameters are constrained, an adaptive approach to terminating subject accrual may improve upon the cost efficiency of a group sequential clinical trial investigating time-to-event endpoints. However, when the spectrum of group sequential designs considered is broadened, the advantage of the adaptive designs is less clear.

Differential adhesion regulates neurite placement via a retrograde zippering mechanism.

During development, neurites and synapses segregate into specific neighborhoods or layers within nerve bundles. The developmental programs guiding placement of neurites in specific layers, and hence their incorporation into specific circuits, are not well understood. We implement novel imaging methods and quantitative models to document the embryonic development of the C. elegans brain neuropil, and discover that differential adhesion mechanisms control precise placement of single neurites onto specific layers. Differential adhesion is orchestrated via developmentally regulated expression of the IgCAM SYG-1, and its partner ligand SYG-2. Changes in SYG-1 expression across neuropil layers result in changes in adhesive forces, which sort SYG-2-expressing neurons. Sorting to layers occurs, not via outgrowth from the neurite tip, but via an alternate mechanism of retrograde zippering, involving interactions between neurite shafts. Our study indicates that biophysical principles from differential adhesion govern neurite placement and synaptic specificity in vivo in developing neuropil bundles.

Developmental expression patterns of protein kinase A catalytic subunits in zebrafish.

Protein kinase A (PKA), also known as cAMP dependent protein kinase, is an essential component of many signaling pathways, many of which regulate key developmental processes. Inactive PKA is a tetrameric holoenzyme, comprised of two catalytic (PRKAC), and two regulatory subunits. Upon cAMP binding, the catalytic subunits are released and thereby activated. There are multiple isoforms of PKA catalytic subunits, but their individual roles are not well understood. In order to begin studying their roles in zebrafish development, it is first necessary to identify the spatial and temporal expression profiles for each prkac subunit. Here we evaluate the expression profiles for the four zebrafish prkacs: prkacαa, αb, ßa, and ßb, at key developmental time points: 24, 48 and 72 h post fertilization. We show that zebrafish prkacs are expressed throughout the developing nervous system, each showing unique expression patterns. This body of work will inform future functional studies into the roles of PKA during development.

Neuronal expression patterns of the PlexinA family during zebrafish development.

Plexins (Plxns) and Semaphorins (Semas) are key signaling molecules that regulate many aspects of development. Plxns are a family of transmembrane protein receptors that are activated upon extracellular binding by Semas. Activated Plxns trigger intracellular signaling cascades, which regulate a range of developmental processes, including axon guidance, neuronal positioning and vasculogenesis. Semas are a large family of both transmembrane and secreted signaling molecules, and show subtype specific binding to different Plxn family members. Each Plxn can play different roles in development, and so tightly regulated temporal and spatial expression of receptor subtypes is critical to ensure appropriate signaling. Here we elucidate the expression profiles of the plxnA family, plxnA1a, A1b, A2, A3 and A4 at 18, 24, 36, 48, 60 and 72 h post fertilization in the developing zebrafish. We show that PlxnA family members are expressed in neuronal tissues during zebrafish development, but exhibit key differences in expression within these tissues. We also highlight that plxnA1 has two genes in zebrafish, A1a and A1b, which show divergences in expression patterns during early development.

Biomarker validation with an imperfect reference: Issues and bounds.

Motivated by the goal of evaluating a biomarker for acute kidney injury, we consider the problem of assessing operating characteristics for a new biomarker when a true gold standard for disease status is unavailable. In this case, the biomarker is typically compared to another imperfect reference test, and this comparison is used to estimate the performance of the new biomarker. However, errors made by the reference test can bias assessment of the new test. Analysis methods like latent class analysis have been proposed to address this issue, generally employing some strong and unverifiable assumptions regarding the relationship between the new biomarker and the reference test. We investigate the conditional independence assumption that is present in many such approaches and show that for a given set of observed data, conditional independence is only possible for a restricted range of disease prevalence values. We explore the information content of the comparison between the new biomarker and the reference test, and give bounds for the true sensitivity and specificity of the new test when operating characteristics for the reference test are known. We demonstrate that in some cases these bounds may be tight enough to provide useful information, but in other cases these bounds may be quite wide.

Fyn-dependent phosphorylation of PlexinA1 and PlexinA2 at conserved tyrosines is essential for zebrafish eye development.

Plexins (Plxns) are semaphorin (Sema) receptors that play important signaling roles, particularly in the developing nervous system and vasculature. Sema-Plxn signaling regulates cellular processes such as cytoskeletal dynamics, proliferation, and differentiation. However, the receptor-proximal signaling mechanisms driving Sema-Plxn signal transduction are only partially understood. Plxn tyrosine phosphorylation is thought to play an important role in these signaling events as receptor and nonreceptor tyrosine kinases have been shown to interact with Plxn receptors. The Src family kinase Fyn can induce the tyrosine phosphorylation of PlxnA1 and PlxnA2. However, the Fyn-dependent phosphorylation sites on these receptors have not been identified. Here, using mass spectrometry-based approaches, we have identified highly conserved, Fyn-induced PlexinA (PlxnA) tyrosine phosphorylation sites. Mutation of these sites to phenylalanine results in significantly decreased Fyn-dependent PlxnA tyrosine phosphorylation. Furthermore, in contrast to wild-type human PLXNA2 mRNA, mRNA harboring these point mutations cannot rescue eye developmental defects when coinjected with a plxnA2 morpholino in zebrafish embryos. Together these data suggest that Fyn-dependent phosphorylation at two critical tyrosines is a key feature of vertebrate PlxnA1 and PlxnA2 signal transduction.