A Network of SLC and ABC Transporter and DME Genes Involved in Remote Sensing and Signaling in the Gut-Liver-Kidney Axis.

Genes central to drug absorption, distribution, metabolism and elimination (ADME) also regulate numerous endogenous molecules. The Remote Sensing and Signaling Hypothesis argues that an ADME gene-centered network-including SLC and ABC "drug" transporters, "drug" metabolizing enzymes (DMEs), and regulatory genes-is essential for inter-organ communication via metabolites, signaling molecules, antioxidants, gut microbiome products, uremic solutes, and uremic toxins. By cross-tissue co-expression network analysis, the gut, liver, and kidney (GLK) formed highly connected tissue-specific clusters of SLC transporters, ABC transporters, and DMEs. SLC22, SLC25 and SLC35 families were network hubs, having more inter-organ and intra-organ connections than other families. Analysis of the GLK network revealed key physiological pathways (e.g., involving bile acids and uric acid). A search for additional genes interacting with the network identified HNF4α, HNF1α, and PXR. Knockout gene expression data confirmed ~60-70% of predictions of ADME gene regulation by these transcription factors. Using the GLK network and known ADME genes, we built a tentative gut-liver-kidney "remote sensing and signaling network" consisting of SLC and ABC transporters, as well as DMEs and regulatory proteins. Together with protein-protein interactions to prioritize likely functional connections, this network suggests how multi-specificity combines with oligo-specificity and mono-specificity to regulate homeostasis of numerous endogenous small molecules

Ten Simple Rules for Reproducible Research in Jupyter Notebooks

Reproducibility of computational studies is a hallmark of scientific methodology. It enables researchers to build with confidence on the methods and findings of others, reuse and extend computational pipelines, and thereby drive scientific progress. Since many experimental studies rely on computational analyses, biologists need guidance on how to set up and document reproducible data analyses or simulations. In this paper, we address several questions about reproducibility. For example, what are the technical and non-technical barriers to reproducible computational studies? What opportunities and challenges do computational notebooks offer to overcome some of these barriers? What tools are available and how can they be used effectively? We have developed a set of rules to serve as a guide to scientists with a specific focus on computational notebook systems, such as Jupyter Notebooks, which have become a tool of choice for many applications. Notebooks combine detailed workflows with narrative text and visualization of results. Combined with software repositories and open source licensing, notebooks are powerful tools for transparent, collaborative, reproducible, and reusable data analyses

Primary Alcohol-Activated Human and Mouse Hepatic Stellate Cells Share Similarities in Gene-Expression Profiles.

Alcoholic liver disease (ALD) is a leading cause of cirrhosis in the United States, which is characterized by extensive deposition of extracellular matrix proteins and formation of a fibrous scar. Hepatic stellate cells (HSCs) are the major source of collagen type 1 producing myofibroblasts in ALD fibrosis. However, the mechanism of alcohol-induced activation of human and mouse HSCs is not fully understood. We compared the gene-expression profiles of primary cultured human HSCs (hHSCs) isolated from patients with ALD (n = 3) or without underlying liver disease (n = 4) using RNA-sequencing analysis. Furthermore, the gene-expression profile of ALD hHSCs was compared with that of alcohol-activated mHSCs (isolated from intragastric alcohol-fed mice) or CCl4-activated mouse HSCs (mHSCs). Comparative transcriptome analysis revealed that ALD hHSCs, in addition to alcohol-activated and CCl4-activated mHSCs, share the expression of common HSC activation (Col1a1 [collagen type I alpha 1 chain], Acta1 [actin alpha 1, skeletal muscle], PAI1 [plasminogen activator inhibitor-1], TIMP1 [tissue inhibitor of metalloproteinase 1], and LOXL2 [lysyl oxidase homolog 2]), indicating that a common mechanism underlies the activation of human and mouse HSCs. Furthermore, alcohol-activated mHSCs most closely recapitulate the gene-expression profile of ALD hHSCs. We identified the genes that are similarly and uniquely up-regulated in primary cultured alcohol-activated hHSCs and freshly isolated mHSCs, which include CSF1R (macrophage colony-stimulating factor 1 receptor), PLEK (pleckstrin), LAPTM5 (lysosmal-associated transmembrane protein 5), CD74 (class I transactivator, the invariant chain), CD53, MMP9 (matrix metallopeptidase 9), CD14, CTSS (cathepsin S), TYROBP (TYRO protein tyrosine kinase-binding protein), and ITGB2 (integrin beta-2), and other genes (compared with CCl4-activated mHSCs). Conclusion: We identified genes in alcohol-activated mHSCs from intragastric alcohol-fed mice that are largely consistent with the gene-expression profile of primary cultured hHSCs from patients with ALD. These genes are unique to alcohol-induced HSC activation in two species, and therefore may become targets or readout for antifibrotic therapy in experimental models of ALD

Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E–09 and 4.10E–18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD

Focal adhesion is associated with lithium response in bipolar disorder: evidence from a network-based multi-omics analysis

Lithium (Li) is one of the most effective drugs for treating bipolar disorder (BD), however, there is presently no way to predict response to guide treatment. The aim of this study is to identify functional genes and pathways that distinguish BD Li responders (LR) from BD Li non-responders (NR). An initial Pharmacogenomics of Bipolar Disorder study (PGBD) GWAS of lithium response did not provide any significant results. As a result, we then employed network-based integrative analysis of transcriptomic and genomic data. In transcriptomic study of iPSC-derived neurons, 41 significantly differentially expressed (DE) genes were identified in LR vs NR regardless of lithium exposure. In the PGBD, post-GWAS gene prioritization using the GWA-boosting (GWAB) approach identified 1119 candidate genes. Following DE-derived network propagation, there was a highly significant overlap of genes between the top 500- and top 2000-proximal gene networks and the GWAB gene list (Phypergeometric = 1.28E–09 and 4.10E–18, respectively). Functional enrichment analyses of the top 500 proximal network genes identified focal adhesion and the extracellular matrix (ECM) as the most significant functions. Our findings suggest that the difference between LR and NR was a much greater effect than that of lithium. The direct impact of dysregulation of focal adhesion on axon guidance and neuronal circuits could underpin mechanisms of response to lithium, as well as underlying BD. It also highlights the power of integrative multi-omics analysis of transcriptomic and genomic profiling to gain molecular insights into lithium response in BD.publishedVersio

Collective Sensing and Information Transfer in Animal Groups

This dissertation addresses several topics in collective motion in animal groups. Coordination among social animals often requires rapid and efficient transfer of information among individuals, which may depend crucially on the underlying structure of the interaction network used for communication. In two experimental systems and in one simulation study, we study the nature of interactions and interaction networks, and how these interactions scale up to global order in the system. The resulting collective properties allow animal groups access to "collective computation" such that they can process and respond to stimuli in ways in which a single individual cannot. First, we study collective evasion maneuvers, manifested through rapid cascades of behavioral change (a ubiquitous behavior among taxa), in schooling fish (Notemigonus crysoleucas). We determine the functional mapping between socially generated sensory input and motor response during collective evasion. We find that individuals employ simple, robust measures to assess behavioral changes in neighbors, and that the resulting networks by which behavior propagates are complex; being weighted and directed. By studying these interaction networks, we reveal the (complex, fractional) nature of social contagion, and establish that individuals with relatively few, but strongly-connected, neighbors are both most socially influential, and most susceptible to influence. Next, we study the relationship between emergent periodic synchronization in ant colonies, and interactions between ants in different behavioral states. We investigate the factors driving fluctuations in the overall level of synchronization observed in the colony, and find that flexible behavioral responses to interactions can explain these fluctuations, in both real data and in a simulated ant colony. Finally, we model collective movement, motivated by experimental data, demonstrating that simple behavioral rules can allow groups to maximize performance in dynamical search tasks. Additionally, the behaviors that optimize performance place the population near a transitional regime. Individuals locate and track dynamic resources by splitting and fusing to form groups that match the length scale of these resources. This occurs even when individuals cannot evaluate resource sizes or determine the sizes of groups to which they belong. Our model demonstrates that fission-fusion dynamics can allow social animals to balance the exploration-exploitation tradeoff