Neil Bahroos

The general mode of translation inhibition by macrolide antibiotics

Significance Macrolide antibiotics inhibit translation by binding in the ribosomal nascent peptide exit tunnel. It was believed that macrolides interfere with protein synthesis by obstructing the egress of nascent proteins. In contrast to this view, the results of ribosome profiling analysis suggest that the main mode of macrolide action is context-specific inhibition of peptide bond formation. The ribosome with a macrolide molecule bound in the tunnel is impaired in catalysis of peptide bond formation between specific combinations of the peptidyl donors and aminoacyl acceptors, leading to interruption of translation when such problematic substrates are encountered. These findings underscore the existence of a link between the ribosomal tunnel and the peptidyl transferase center and pave the way for development of superior antibiotics. Macrolides are clinically important antibiotics thought to inhibit bacterial growth by impeding the passage of newly synthesized polypeptides through the nascent peptide exit tunnel of the bacterial ribosome. Recent data challenged this view by showing that macrolide antibiotics can differentially affect synthesis of individual proteins. To understand the general mechanism of macrolide action, we used genome-wide ribosome profiling and analyzed the redistribution of ribosomes translating highly expressed genes in bacterial cells treated with high concentrations of macrolide antibiotics. The metagene analysis indicated that inhibition of early rounds of translation, which would be characteristic of the conventional view of macrolide action, occurs only at a limited number of genes. Translation of most genes proceeds past the 5′-proximal codons and can be arrested at more distal codons when the ribosome encounters specific short sequence motifs. The problematic sequence motifs are confined to the nascent peptide residues in the peptidyl transferase center but not to the peptide segment that contacts the antibiotic molecule in the exit tunnel. Therefore, it appears that the general mode of macrolide action involves selective inhibition of peptide bond formation between specific combinations of donor and acceptor substrates. Additional factors operating in the living cell but not functioning during in vitro protein synthesis may modulate site-specific action of macrolide antibiotics.

APOE‐modulated Aβ‐induced neuroinflammation in Alzheimer's disease: current landscape, novel data, and future perspective

Chronic glial activation and neuroinflammation induced by the amyloid‐β peptide (Aβ) contribute to Alzheimers disease (AD) pathology. APOE4 is the greatest AD‐genetic risk factor; increasing risk up to 12‐fold compared to APOE3, with APOE4‐specific neuroinflammation an important component of this risk. This editorial review discusses the role of APOE in inflammation and AD, via a literature review, presentation of novel data on Aβ‐induced neuroinflammation, and discussion of future research directions. The complexity of chronic neuroinflammation, including multiple detrimental and beneficial effects occurring in a temporal and cell‐specific manner, has resulted in conflicting functional data for virtually every inflammatory mediator. Defining a neuroinflammatory phenotype (NIP) is one way to address this issue, focusing on profiling the changes in inflammatory mediator expression during disease progression. Although many studies have shown that APOE4 induces a detrimental NIP in peripheral inflammation and Aβ‐independent neuroinflammation, data for APOE‐modulated Aβ‐induced neuroinflammation are surprisingly limited. We present data supporting the hypothesis that impaired apoE4 function modulates Aβ‐induced effects on inflammatory receptor signaling, including amplification of detrimental (toll‐like receptor 4‐p38α) and suppression of beneficial (IL‐4R‐nuclear receptor) pathways. To ultimately develop APOE genotype‐specific therapeutics, it is critical that future studies define the dynamic NIP profile and pathways that underlie APOE‐modulated chronic neuroinflammation. In this editorial review, we present data supporting the hypothesis that impaired apoE4 function modulates Aβ‐induced effects on inflammatory receptor signaling, including amplification of detrimental (TLR4‐p38α) and suppression of beneficial (IL‐4R‐nuclear receptor) pathways, resulting in an adverse NIP that causes neuronal dysfunction. NIP, Neuroinflammatory phenotype; P.I., pro‐inflammatory; A.I., anti‐inflammatory.

The discriminatory cost of ICD-10-CM transition between clinical specialties: metrics, case study, and mitigating tools

Objective Applying the science of networks to quantify the discriminatory impact of the ICD-9-CM to ICD-10-CM transition between clinical specialties. Materials and Methods Datasets were the Center for Medicaid and Medicare Services ICD-9-CM to ICD-10-CM mapping files, general equivalence mappings, and statewide Medicaid emergency department billing. Diagnoses were represented as nodes and their mappings as directional relationships. The complex network was synthesized as an aggregate of simpler motifs and tabulation per clinical specialty. Results We identified five mapping motif categories: identity, class-to-subclass, subclass-to-class, convoluted, and no mapping. Convoluted mappings indicate that multiple ICD-9-CM and ICD-10-CM codes share complex, entangled, and non-reciprocal mappings. The proportions of convoluted diagnoses mappings (36% overall) range from 5% (hematology) to 60% (obstetrics and injuries). In a case study of 24 008 patient visits in 217 emergency departments, 27% of the costs are associated with convoluted diagnoses, with ‘abdominal pain’ and ‘gastroenteritis’ accounting for approximately 3.5%. Discussion Previous qualitative studies report that administrators and clinicians are likely to be challenged in understanding and managing their practice because of the ICD-10-CM transition. We substantiate the complexity of this transition with a thorough quantitative summary per clinical specialty, a case study, and the tools to apply this methodology easily to any clinical practice in the form of a web portal and analytic tables. Conclusions Post-transition, successful management of frequent diseases with convoluted mapping network patterns is critical. The http://lussierlab.org/transition-to-ICD10CM web portal provides insight in linking onerous diseases to the ICD-10 transition.

'N-of-1-pathways' unveils personal deregulated mechanisms from a single pair of RNA-Seq samples: towards precision medicine.

Background The emergence of precision medicine allowed the incorporation of individual molecular data into patient care. Indeed, DNA sequencing predicts somatic mutations in individual patients. However, these genetic features overlook dynamic epigenetic and phenotypic response to therapy. Meanwhile, accurate personal transcriptome interpretation remains an unmet challenge. Further, N-of-1 (single-subject) efficacy trials are increasingly pursued, but are underpowered for molecular marker discovery. Method ‘N-of-1-pathways’ is a global framework relying on three principles: (i) the statistical universe is a single patient; (ii) significance is derived from geneset/biomodules powered by paired samples from the same patient; and (iii) similarity between genesets/biomodules assesses commonality and differences, within-study and cross-studies. Thus, patient gene-level profiles are transformed into deregulated pathways. From RNA-Seq of 55 lung adenocarcinoma patients, N-of-1-pathways predicts the deregulated pathways of each patient. Results Cross-patient N-of-1-pathways obtains comparable results with conventional genesets enrichment analysis (GSEA) and differentially expressed gene (DEG) enrichment, validated in three external evaluations. Moreover, heatmap and star plots highlight both individual and shared mechanisms ranging from molecular to organ-systems levels (eg, DNA repair, signaling, immune response). Patients were ranked based on the similarity of their deregulated mechanisms to those of an independent gold standard, generating unsupervised clusters of diametric extreme survival phenotypes (p=0.03). Conclusions The N-of-1-pathways framework provides a robust statistical and relevant biological interpretation of individual disease-free survival that is often overlooked in conventional cross-patient studies. It enables mechanism-level classifiers with smaller cohorts as well as N-of-1 studies. Software http://lussierlab.org/publications/N-of-1-pathways

CAPriCORN: Chicago Area Patient-Centered Outcomes Research Network

The Chicago Area Patient-Centered Outcomes Research Network (CAPriCORN) represents an unprecedented collaboration across diverse healthcare institutions including private, county, and state hospitals and health systems, a consortium of Federally Qualified Health Centers, and two Department of Veterans Affairs hospitals. CAPriCORN builds on the strengths of our institutions to develop a cross-cutting infrastructure for sustainable and patient-centered comparative effectiveness research in Chicago. Unique aspects include collaboration with the University HealthSystem Consortium to aggregate data across sites, a centralized communication center to integrate patient recruitment with the data infrastructure, and a centralized institutional review board to ensure a strong and efficient human subject protection program. With coordination by the Chicago Community Trust and the Illinois Medical District Commission, CAPriCORN will model how healthcare institutions can overcome barriers of data integration, marketplace competition, and care fragmentation to develop, test, and implement strategies to improve care for diverse populations and reduce health disparities.

Nitric Oxide Regulates Gene Expression in Cancers by Controlling Histone Posttranslational Modifications

Altered nitric oxide (•NO) metabolism underlies cancer pathology, but mechanisms explaining many •NO-associated phenotypes remain unclear. We have found that cellular exposure to •NO changes histone posttranslational modifications (PTM) by directly inhibiting the catalytic activity of JmjC-domain containing histone demethylases. Herein, we describe how •NO exposure links modulation of histone PTMs to gene expression changes that promote oncogenesis. Through high-resolution mass spectrometry, we generated an extensive map of •NO-mediated histone PTM changes at 15 critical lysine residues on the core histones H3 and H4. Concomitant microarray analysis demonstrated that exposure to physiologic •NO resulted in the differential expression of over 6,500 genes in breast cancer cells. Measurements of the association of H3K9me2 and H3K9ac across genomic loci revealed that differential distribution of these particular PTMs correlated with changes in the level of expression of numerous oncogenes, consistent with epigenetic code. Our results establish that •NO functions as an epigenetic regulator of gene expression mediated by changes in histone PTMs.

Histone reader BRWD1 targets and restricts recombination to the Igk locus.

B lymphopoiesis requires that immunoglobulin genes be accessible to RAG1-RAG2 recombinase. However, the RAG proteins bind widely to open chromatin, which suggests that additional mechanisms must restrict RAG-mediated DNA cleavage. Here we show that developmental downregulation of interleukin 7 (IL-7)-receptor signaling in small pre-B cells induced expression of the bromodomain-family member BRWD1, which was recruited to a specific epigenetic landscape at Igk dictated by pre-B cell receptor (pre-BCR)-dependent Erk activation. BRWD1 enhanced RAG recruitment, increased gene accessibility and positioned nucleosomes 5′ to each Jκ recombination signal sequence. BRWD1 thus targets recombination to Igk and places recombination within the context of signaling cascades that control B cell development. Our findings represent a paradigm in which, at any particular antigen-receptor locus, specialized mechanisms enforce lineage- and stage-specific recombination.

Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data

Robust methods for identifying patterns of expression in genome-wide data are important for generating hypotheses regarding gene function. To this end, several analytic methods have been developed for detecting periodic patterns. We improve one such method, JTK_CYCLE, by explicitly calculating the null distribution such that it accounts for multiple hypothesis testing and by including non-sinusoidal reference waveforms. We term this method empirical JTK_CYCLE with asymmetry search, and we compare its performance to JTK_CYCLE with Bonferroni and Benjamini-Hochberg multiple hypothesis testing correction, as well as to five other methods: cyclohedron test, address reduction, stable persistence, ANOVA, and F24. We find that ANOVA, F24, and JTK_CYCLE consistently outperform the other three methods when data are limited and noisy; empirical JTK_CYCLE with asymmetry search gives the greatest sensitivity while controlling for the false discovery rate. Our analysis also provides insight into experimental design and we find that, for a fixed number of samples, better sensitivity and specificity are achieved with higher numbers of replicates than with higher sampling density. Application of the methods to detecting circadian rhythms in a metadataset of microarrays that quantify time-dependent gene expression in whole heads of Drosophila melanogaster reveals annotations that are enriched among genes with highly asymmetric waveforms. These include a wide range of oxidation reduction and metabolic genes, as well as genes with transcripts that have multiple splice forms.

Metrics and tools for consistent cohort discovery and financial analyses post-transition to ICD-10-CM

In the United States, International Classification of Disease Clinical Modification (ICD-9-CM, the ninth revision) diagnosis codes are commonly used to identify patient cohorts and to conduct financial analyses related to disease. In October 2015, the healthcare system of the United States will transition to ICD-10-CM (the tenth revision) diagnosis codes. One challenge posed to clinical researchers and other analysts is conducting diagnosis-related queries across datasets containing both coding schemes. Further, healthcare administrators will manage growth, trends, and strategic planning with these dually-coded datasets. The majority of the ICD-9-CM to ICD-10-CM translations are complex and nonreciprocal, creating convoluted representations and meanings. Similarly, mapping back from ICD-10-CM to ICD-9-CM is equally complex, yet different from mapping forward, as relationships are likewise nonreciprocal. Indeed, 10 of the 21 top clinical categories are complex as 78% of their diagnosis codes are labeled as “convoluted” by our analyses. Analysis and research related to external causes of morbidity, injury, and poisoning will face the greatest challenges due to 41 745 (90%) convolutions and a decrease in the number of codes. We created a web portal tool and translation tables to list all ICD-9-CM diagnosis codes related to the specific input of ICD-10-CM diagnosis codes and their level of complexity: “identity” (reciprocal), “class-to-subclass,” “subclass-to-class,” “convoluted,” or “no mapping.” These tools provide guidance on ambiguous and complex translations to reveal where reports or analyses may be challenging to impossible. Web portal: http://www.lussierlab.org/transition-to-ICD9CM/ Tables annotated with levels of translation complexity: http://www.lussierlab.org/publications/ICD10to9

Human Lacrimal Gland Gene Expression

Background The study of human lacrimal gland biology and development is limited. Lacrimal gland tissue is damaged or poorly functional in a number of disease states including dry eye disease. Development of cell based therapies for lacrimal gland diseases requires a better understanding of the gene expression and signaling pathways in lacrimal gland. Differential gene expression analysis between lacrimal gland and other embryologically similar tissues may be helpful in furthering our understanding of lacrimal gland development. Methods We performed global gene expression analysis of human lacrimal gland tissue using Affymetrix ® gene expression arrays. Primary data from our laboratory was compared with datasets available in the NLM GEO database for other surface ectodermal tissues including salivary gland, skin, conjunctiva and corneal epithelium. Results The analysis revealed statistically significant difference in the gene expression of lacrimal gland tissue compared to other ectodermal tissues. The lacrimal gland specific, cell surface secretory protein encoding genes and critical signaling pathways which distinguish lacrimal gland from other ectodermal tissues are described. Conclusions Differential gene expression in human lacrimal gland compared with other ectodermal tissue types revealed interesting patterns which may serve as the basis for future studies in directed differentiation among other areas.