HieRFIT: a hierarchical cell type classification tool for projections from complex single-cell atlas datasets.

MOTIVATION: The emergence of single-cell RNA sequencing (scRNA-seq) has led to an explosion in novel methods to study biological variation among individual cells, and to classify cells into functional and biologically meaningful categories. RESULTS: Here, we present a new cell type projection tool, Hierarchical Random Forest for Information Transfer (HieRFIT), based on hierarchical random forests. HieRFIT uses a priori information about cell type relationships to improve classification accuracy, taking as input a hierarchical tree structure representing the class relationships, along with the reference data. We use an ensemble approach combining multiple random forest models, organized in a hierarchical decision tree structure. We show that our hierarchical classification approach improves accuracy and reduces incorrect predictions especially for inter-dataset tasks which reflect real-life applications. We use a scoring scheme that adjusts probability distributions for candidate class labels and resolves uncertainties while avoiding the assignment of cells to incorrect types by labeling cells at internal nodes of the hierarchy when necessary. AVAILABILITY AND IMPLEMENTATION: HieRFIT is implemented as an R package, and it is available at (https://github.com/yasinkaymaz/HieRFIT/releases/tag/v1.0.0). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

REM sleep's unique associations with corticosterone regulation, apoptotic pathways, and behavior in chronic stress in mice.

One of sleep's putative functions is mediation of adaptation to waking experiences. Chronic stress is a common waking experience; however, which specific aspect of sleep is most responsive, and how sleep changes relate to behavioral disturbances and molecular correlates remain unknown. We quantified sleep, physical, endocrine, and behavioral variables, as well as the brain and blood transcriptome in mice exposed to 9 weeks of unpredictable chronic mild stress (UCMS). Comparing 46 phenotypic variables revealed that rapid-eye-movement sleep (REMS), corticosterone regulation, and coat state were most responsive to UCMS. REMS theta oscillations were enhanced, whereas delta oscillations in non-REMS were unaffected. Transcripts affected by UCMS in the prefrontal cortex, hippocampus, hypothalamus, and blood were associated with inflammatory and immune responses. A machine-learning approach controlling for unspecific UCMS effects identified transcriptomic predictor sets for REMS parameters that were enriched in 193 pathways, including some involved in stem cells, immune response, and apoptosis and survival. Only three pathways were enriched in predictor sets for non-REMS. Transcriptomic predictor sets for variation in REMS continuity and theta activity shared many pathways with corticosterone regulation, in particular pathways implicated in apoptosis and survival, including mitochondrial apoptotic machinery. Predictor sets for REMS and anhedonia shared pathways involved in oxidative stress, cell proliferation, and apoptosis. These data identify REMS as a core and early element of the response to chronic stress, and identify apoptosis and survival pathways as a putative mechanism by which REMS may mediate the response to stressful waking experiences.

Accurate characterization of the IFITM locus using MiSeq and PacBio sequencing shows genetic variation in Galliformes.

BACKGROUND: Interferon inducible transmembrane (IFITM) proteins are effectors of the immune system widely characterized for their role in restricting infection by diverse enveloped and non-enveloped viruses. The chicken IFITM (chIFITM) genes are clustered on chromosome 5 and to date four genes have been annotated, namely chIFITM1, chIFITM3, chIFITM5 and chIFITM10. However, due to poor assembly of this locus in the Gallus Gallus v4 genome, accurate characterization has so far proven problematic. Recently, a new chicken reference genome assembly Gallus Gallus v5 was generated using Sanger, 454, Illumina and PacBio sequencing technologies identifying considerable differences in the chIFITM locus over the previous genome releases. METHODS: We re-sequenced the locus using both Illumina MiSeq and PacBio RS II sequencing technologies and we mapped RNA-seq data from the European Nucleotide Archive (ENA) to this finalized chIFITM locus. Using SureSelect probes capture probes designed to the finalized chIFITM locus, we sequenced the locus of a different chicken breed, namely a White Leghorn, and a turkey. RESULTS: We confirmed the Gallus Gallus v5 consensus except for two insertions of 5 and 1 base pair within the chIFITM3 and B4GALNT4 genes, respectively, and a single base pair deletion within the B4GALNT4 gene. The pull down revealed a single amino acid substitution of A63V in the CIL domain of IFITM2 compared to Red Jungle fowl and 13, 13 and 11 differences between IFITM1, 2 and 3 of chickens and turkeys, respectively. RNA-seq shows chIFITM2 and chIFITM3 expression in numerous tissue types of different chicken breeds and avian cell lines, while the expression of the putative chIFITM1 is limited to the testis, caecum and ileum tissues. CONCLUSIONS: Locus resequencing using these capture probes and RNA-seq based expression analysis will allow the further characterization of genetic diversity within Galliformes.

BrainTACO: an explorable multi-scale multi-modal brain transcriptomic and connectivity data resource.

Exploring the relationships between genes and brain circuitry can be accelerated by joint analysis of heterogeneous datasets from 3D imaging data, anatomical data, as well as brain networks at varying scales, resolutions, and modalities. Generating an integrated view, beyond the individual resources' original purpose, requires the fusion of these data to a common space, and a visualization that bridges the gap across scales. However, despite ever expanding datasets, few platforms for integration and exploration of this heterogeneous data exist. To this end, we present the BrainTACO (Brain Transcriptomic And Connectivity Data) resource, a selection of heterogeneous, and multi-scale neurobiological data spatially mapped onto a common, hierarchical reference space, combined via a holistic data integration scheme. To access BrainTACO, we extended BrainTrawler, a web-based visual analytics framework for spatial neurobiological data, with comparative visualizations of multiple resources. This enables gene expression dissection of brain networks with, to the best of our knowledge, an unprecedented coverage and allows for the identification of potential genetic drivers of connectivity in both mice and humans that may contribute to the discovery of dysconnectivity phenotypes. Hence, BrainTACO reduces the need for time-consuming manual data aggregation often required for computational analyses in script-based toolboxes, and supports neuroscientists by directly leveraging the data instead of preparing it.

Knowledge Graphs for Indication Expansion: An Explainable Target-Disease Prediction Method.

Indication expansion aims to find new indications for existing targets in order to accelerate the process of launching a new drug for a disease on the market. The rapid increase in data types and data sources for computational drug discovery has fostered the use of semantic knowledge graphs (KGs) for indication expansion through target centric approaches, or in other words, target repositioning. Previously, we developed a novel method to construct a KG for indication expansion studies, with the aim of finding and justifying alternative indications for a target gene of interest. In contrast to other KGs, ours combines human-curated full-text literature and gene expression data from biomedical databases to encode relationships between genes, diseases, and tissues. Here, we assessed the suitability of our KG for explainable target-disease link prediction using a glass-box approach. To evaluate the predictive power of our KG, we applied shortest path with tissue information- and embedding-based prediction methods to a graph constructed with information published before or during 2010. We also obtained random baselines by applying the shortest path predictive methods to KGs with randomly shuffled node labels. Then, we evaluated the accuracy of the top predictions using gene-disease links reported after 2010. In addition, we investigated the contribution of the KG's tissue expression entity to the prediction performance. Our experiments showed that shortest path-based methods significantly outperform the random baselines and embedding-based methods outperform the shortest path predictions. Importantly, removing the tissue expression entity from the KG severely impacts the quality of the predictions, especially those produced by the embedding approaches. Finally, since the interpretability of the predictions is crucial in indication expansion, we highlight the advantages of our glass-box model through the examination of example candidate target-disease predictions.

CRISPR/Cas9-mediated Knockout of the Neuropsychiatric Risk Gene KCTD13 Causes Developmental Deficits in Human Cortical Neurons Derived from Induced Pluripotent Stem Cells.

The human KCTD13 gene is located within the 16p11.2 locus and copy number variants of this locus are associated with a high risk for neuropsychiatric diseases including autism spectrum disorder and schizophrenia. Studies in zebrafish point to a role of KCTD13 in proliferation of neural precursor cells which may contribute to macrocephaly in 16p11.2 deletion carriers. KCTD13 is highly expressed in the fetal human brain and in mouse cortical neurons, but its contribution to the development and function of mammalian neurons is not completely understood. In the present study, we deleted the KCTD13 gene in human-induced pluripotent stem cells (iPSCs) using CRISPR/Cas9 nickase. Following neural differentiation of KCTD13 deficient and isogenic control iPSC lines, we detected a moderate but significant inhibition of DNA synthesis and proliferation in KCTD13 deficient human neural precursor cells. KCTD13 deficient cortical neurons derived from iPSCs showed decreased neurite formation and reduced spontaneous network activity. RNA-sequencing and pathway analysis pointed to a role for ERBB signaling in these phenotypic changes. Consistently, activating and inhibiting ERBB kinases rescued and aggravated, respectively, impaired neurite formation. In contrast to findings in non-neuronal human HeLa cells, we did not detect an accumulation of the putative KCTD13/Cullin-3 substrate RhoA, and treatment with inhibitors of RhoA signaling did not rescue decreased neurite formation in human KCTD13 knockout neurons. Taken together, our data provide insight into the role of KCTD13 in neurodevelopmental disorders, and point to ERBB signaling as a potential target for neuropsychiatric disorders associated with KCTD13 deficiency.

Strategies to optimize medication use in the physician group practice: the role of the clinical pharmacist.

OBJECTIVES: To (1) describe the role of clinical pharmacists in providing population-based pharmaceutical care as employees of a physician group practice, (2) describe the strategies used by pharmacists to optimize medication use, (3) quantify improvements in care, and (4) illustrate the calculations used to quantify cost savings. SETTING: Community-based, multispecialty, physician group practice located in the north Puget Sound area between 2003 and 2007. PRACTICE DESCRIPTION: Using four cornerstones (evidence-based medicine, therapeutic interchange, academic detailing, and a local pharmacy and therapeutics committee), the pharmacists provided population-based pharmaceutical care, leading generic switches, target drug programs, and prescription to over-the-counter medication switches. They also led disease management programs, managed drug recalls, implemented electronic health records, negotiated budgets with health plans, and led patient assistance programs and prior authorization programs to improve patient satisfaction. PRACTICE INNOVATION: Implementing these strategies from the vantage point of a physician group presents a seldom-realized employment opportunity for pharmacists. MAIN OUTCOME MEASURES: The impact of these strategies is measured by process, use, and clinical outcomes metrics. These, in turn, are linked to incentive payments in the pay-for-performance environment or to a lowered per member, per month cost in the capitated environment. RESULTS: In 2006-2007, 71% of our hypertensive patients received generic agents compared with a network average for receiving generic agents of 43%, while the proportion of patients with controlled blood pressure increased from 45% to 60%. We saved $450,000 in inpatient costs for deep venous thrombosis. CONCLUSION: Clinical pharmacists employed in a physician group practice can optimize medication use, improve care, and reduce costs.

Loss of Trem2 in microglia leads to widespread disruption of cell coexpression networks in mouse brain.

Rare heterozygous coding variants in the triggering receptor expressed in myeloid cells 2 (TREM2) gene, conferring increased risk of developing late-onset Alzheimer's disease, have been identified. We examined the transcriptional consequences of the loss of Trem2 in mouse brain to better understand its role in disease using differential expression and coexpression network analysis of Trem2 knockout and wild-type mice. We generated RNA-Seq data from cortex and hippocampus sampled at 4 and 8 months. Using brain cell-type markers and ontology enrichment, we found subnetworks with cell type and/or functional identity. We primarily discovered changes in an endothelial gene-enriched subnetwork at 4 months, including a shift toward a more central role for the amyloid precursor protein gene, coupled with widespread disruption of other cell-type subnetworks, including a subnetwork with neuronal identity. We reveal an unexpected potential role of Trem2 in the homeostasis of endothelial cells that goes beyond its known functions as a microglial receptor and signaling hub, suggesting an underlying link between immune response and vascular disease in dementia.

The impact of e-prescribing on prescriber and staff time in ambulatory care clinics: a time motion study.

Electronic prescribing has improved the quality and safety of care. One barrier preventing widespread adoption is the potential detrimental impact on workflow. We used time-motion techniques to compare prescribing times at three ambulatory care sites that used paper-based prescribing, desktop, or laptop e-prescribing. An observer timed all prescriber (n = 27) and staff (n = 42) tasks performed during a 4-hour period. At the sites with optional e-prescribing >75% of prescription-related events were performed electronically. Prescribers at e-prescribing sites spent less time writing, but time-savings were offset by increased computer tasks. After adjusting for site, prescriber and prescription type, e-prescribing tasks took marginally longer than hand written prescriptions (12.0 seconds; -1.6, 25.6 CI). Nursing staff at the e-prescribing sites spent longer on computer tasks (5.4 minutes/hour; 0.0, 10.7 CI). E-prescribing was not associated with an increase in combined computer and writing time for prescribers. If carefully implemented, e-prescribing will not greatly disrupt workflow.

Characterization of prescribing errors in an internal medicine clinic.

PURPOSE: A pilot study was conducted to characterize the epidemiology of prescribing errors, comparing those that occurred pre- to postimplementation of an electronic prescribing system; this article describes the results of the study during the preimplementation phase, when a handwritten prescription process was still in place. SUMMARY: A retrospective review of 1411 prescriptions that were handwritten during a five-month time frame was used to identify and characterize medication errors and potential medication errors. The review was conducted in an internal medicine clinic in a large health system that was preparing to implement an electronic prescribing system. The first phase was the implementation of a basic system-one that facilitated the writing of a more complete and legible prescription. The second phase consisted of adding more sophisticated clinical decision support (CDS) capabilities. Three data sources were reviewed: the handwritten prescription, the electronic health record and the prescription as it had been entered into the pharmacy computer system. Almost 28% of the prescriptions evaluated contained one or more errors or potential errors. Over 90% of the errors were potential errors. Only 0.2% of the errors caused patient harm. Non-clinical errors (illegibility, missing information, wrong dose) may be affected by a basic electronic prescribing system, and clinical errors (drug-disease interaction, contraindication of a drug) may be affected only when more sophisticated levels of CDS programming are added. CONCLUSION: Potential prescribing errors occurred frequently but few reached the patient or caused harm. The most severe errors were those that may be reduced by the implementation of an electronic prescribing system with CDS capabilities.

The Role of microRNAs in Bovine Infection and Immunity.

MicroRNAs (miRNAs) are a class of small, non-coding RNAs that are recognized as critical regulators of immune gene expression during infection. Many immunologically significant human miRNAs have been found to be conserved in agriculturally important species, including cattle. Discovering how bovine miRNAs mediate the immune defense during infection is critical to understanding the etiology of the most prevalent bovine diseases. Here, we review current knowledge of miRNAs in the bovine genome, and discuss the advances in understanding of miRNAs as regulators of immune cell function, and bovine immune response activation, regulation, and resolution. Finally, we consider the future perspectives on miRNAs in bovine viral disease, their role as potential biomarkers and in therapy.

MicroRNA regulation of bovine monocyte inflammatory and metabolic networks in an in vivo infection model.

Bovine mastitis is an inflammation-driven disease of the bovine mammary gland that costs the global dairy industry several billion dollars per year. Because disease susceptibility is a multifactorial complex phenotype, an integrative biology approach is required to dissect the molecular networks involved. Here, we report such an approach using next-generation sequencing combined with advanced network and pathway biology methods to simultaneously profile mRNA and miRNA expression at multiple time points (0, 12, 24, 36 and 48 hr) in milk and blood FACS-isolated CD14(+) monocytes from animals infected in vivo with Streptococcus uberis. More than 3700 differentially expressed (DE) genes were identified in milk-isolated monocytes (MIMs), a key immune cell recruited to the site of infection during mastitis. Upregulated genes were significantly enriched for inflammatory pathways, whereas downregulated genes were enriched for nonglycolytic metabolic pathways. Monocyte transcriptional changes in the blood, however, were more subtle but highlighted the impact of this infection systemically. Genes upregulated in blood-isolated monocytes (BIMs) showed a significant association with interferon and chemokine signaling. Furthermore, 26 miRNAs were DE in MIMs and three were DE in BIMs. Pathway analysis revealed that predicted targets of downregulated miRNAs were highly enriched for roles in innate immunity (FDR < 3.4E-8), particularly TLR signaling, whereas upregulated miRNAs preferentially targeted genes involved in metabolism. We conclude that during S. uberis infection miRNAs are key amplifiers of monocyte inflammatory response networks and repressors of several metabolic pathways.

Structural bioinformatics and protein docking analysis of the molecular chaperone-kinase interactions: towards allosteric inhibition of protein kinases by targeting the hsp90-cdc37 chaperone machinery.

A fundamental role of the Hsp90-Cdc37 chaperone system in mediating maturation of protein kinase clients and supporting kinase functional activity is essential for the integrity and viability of signaling pathways involved in cell cycle control and organism development. Despite significant advances in understanding structure and function of molecular chaperones, the molecular mechanisms and guiding principles of kinase recruitment to the chaperone system are lacking quantitative characterization. Structural and thermodynamic characterization of Hsp90-Cdc37 binding with protein kinase clients by modern experimental techniques is highly challenging, owing to a transient nature of chaperone-mediated interactions. In this work, we used experimentally-guided protein docking to probe the allosteric nature of the Hsp90-Cdc37 binding with the cyclin-dependent kinase 4 (Cdk4) kinase clients. The results of docking simulations suggest that the kinase recognition and recruitment to the chaperone system may be primarily determined by Cdc37 targeting of the N-terminal kinase lobe. The interactions of Hsp90 with the C-terminal kinase lobe may provide additional "molecular brakes" that can lock (or unlock) kinase from the system during client loading (release) stages. The results of this study support a central role of the Cdc37 chaperone in recognition and recruitment of the kinase clients. Structural analysis may have useful implications in developing strategies for allosteric inhibition of protein kinases by targeting the Hsp90-Cdc37 chaperone machinery.

Next generation sequencing reveals the expression of a unique miRNA profile in response to a gram-positive bacterial infection.

MicroRNAs (miRNAs) are short, non-coding RNAs, which post-transcriptionally regulate gene expression and are proposed to play a key role in the regulation of innate and adaptive immunity. Here, we report a next generation sequencing (NGS) approach profiling the expression of miRNAs in primary bovine mammary epithelial cells (BMEs) at 1, 2, 4 and 6 hours post-infection with Streptococcus uberis, a causative agent of bovine mastitis. Analysing over 450 million sequencing reads, we found that 20% of the approximately 1,300 currently known bovine miRNAs are expressed in unchallenged BMEs. We also identified the expression of more than 20 potentially novel bovine miRNAs. There is, however, a significant dynamic range in the expression of known miRNAs. The top 10 highly expressed miRNAs account for >80% of all aligned reads, with the remaining miRNAs showing much lower expression. Twenty-one miRNAs were identified as significantly differentially expressed post-infection with S. uberis. Several of these miRNAs have characterised roles in the immune systems of other species. This miRNA response to the Gram-positive S. uberis is markedly different, however, to lipopolysaccharide (LPS) induced miRNA expression. Of 145 miRNAs identified in the literature as being LPS responsive, only 9 were also differentially expressed in response to S. uberis. Computational analysis has also revealed that the predicted target genes of miRNAs, which are down-regulated in BMEs following S. uberis infection, are statistically enriched for roles in innate immunity. This suggests that miRNAs, which potentially act as central regulators of gene expression responses to a Gram-positive bacterial infection, may significantly regulate the sentinel capacity of mammary epithelial cells to mobilise the innate immune system.

Electronic prescribing at the point of care: a time-motion study in the primary care setting.

OBJECTIVE: To evaluate the impact of an ambulatory computerized provider order entry (CPOE ) system on the time efficiency of prescribers. Two primary aims were to compare prescribing time between (1) handwritten and electronic (e-) prescriptions and (2) e-prescriptions using differing hardware configurations. DATA SOURCES/STUDY SETTING: Primary data on prescribers/staff were collected (2005-2007) at three primary care clinics in a community based, multispecialty health system. STUDY DESIGN: This was a quasi-experimental, direct observation, time-motion study conducted in two phases. In phase 1 (n=69 subjects), each site used a unique combination of CPOE software/hardware (paper-based, desktops in prescriber offices or hallway workstations, or laptops). In phase 2 (n=77), all sites used CPOE software on desktops in examination rooms (at point of care). DATA COLLECTION METHODS: Data were collected using TimerPro software on a Palm device. PRINCIPAL FINDINGS: Average time to e-prescribe using CPOE in the examination room was 69 seconds/prescription-event (new/renewed combined)-25 seconds longer than to handwrite (99.5 percent confidence interval [CI] 12.38), and 24 seconds longer than to e-prescribe at offices/workstations (99.5 percent CI 8.39). Each calculates to 20 seconds longer per patient. CONCLUSIONS: E-prescribing takes longer than handwriting. E-prescribing at the point of care takes longer than e-prescribing in offices/workstations. Improvements in safety and quality may be worth the investment of time.