Cross-species gene expression analysis of species specific differences in the preclinical assessment of pharmaceutical compounds

Annotation depth confounds direct comparison of gene expression across species

BACKGROUND

Comparisons of the molecular framework among organisms can be done on both structural and functional levels. One of the most common top-down approaches for functional comparisons is RNA sequencing. This estimation of organismal transcriptional responses is of interest for understanding evolution of molecular activity, which is used for answering a diversity of questions ranging from basic biology to pre-clinical species selection and translation. However, direct comparison between species is often hindered by evolutionary divergence in structure of molecular framework, as well as large difference in the depth of our understanding of the genetic background between humans and other species. Here, we focus on the latter. We attempt to understand how differences in transcriptome annotation affect direct gene abundance comparisons between species.

RESULTS

We examine and suggest some straightforward approaches for direct comparison given the current available tools and using a sample dataset from human, cynomolgus monkey, dog, rat and mouse with a common quantitation and normalization approach. In addition, we examine how variation in genome annotation depth and quality across species may affect these direct comparisons.

CONCLUSIONS

Our findings suggest that further efforts for better genome annotation or computational normalization tools may be of strong interest.

Systemic PFOS and PFOA exposure and disturbed lipid homeostasis in humans: what do we know and what not?

Associations between per- and polyfluoroalkyl substances (PFASs) and increased blood lipids have been repeatedly observed in humans, but a causal relation has been debated. Rodent studies show reverse effects, i.e. decreased blood cholesterol and triglycerides, occurring however at PFAS serum levels at least 100-fold higher than those in humans. This paper aims to present the main issues regarding the modulation of lipid homeostasis by the two most common PFASs, PFOS and PFOA, with emphasis on the underlying mechanisms relevant for humans. Overall, the apparent contrast between human and animal data may be an artifact of dose, with different molecular pathways coming into play upon exposure to PFASs at very low versus high levels. Altogether, the interpretation of existing rodent data on PFOS/PFOA-induced lipid perturbations with respect to the human situation is complex. From a mechanistic perspective, research on human liver cells shows that PFOS/PFOA activate the PPARα pathway, whereas studies on the involvement of other nuclear receptors, like PXR, are less conclusive. Other data indicate that suppression of the nuclear receptor HNF4α signaling pathway, as well as perturbations of bile acid metabolism and transport might be important cellular events that require further investigation. Future studies with human-relevant test systems would help to obtain more insight into the mechanistic pathways pertinent for humans. These studies shall be designed with a careful consideration of appropriate dosing and toxicokinetics, so as to enable biologically plausible quantitative extrapolations. Such research will increase the understanding of possible perturbed lipid homeostasis related to PFOS/ PFOA exposure and the potential implications for human health.

Drugs linked to plasma homoarginine in chronic kidney disease patients—a cross-sectional analysis of the German Chronic Kidney Disease cohort

Background

Elevated plasma concentrations of symmetric and asymmetric dimethylarginine (SDMA and ADMA, respectively) and a lower plasma concentration of the structurally related homoarginine are commonly observed in patients with chronic kidney disease (CKD) and independently predict total mortality as well as progression of renal disease. We aimed to identify drugs that may alter this adverse metabolite pattern in a favourable fashion.

Methods

Plasma ADMA, SDMA, homoarginine and l-arginine were determined by liquid chromatography–tandem mass spectrometry in 4756 CKD patients ages 18–74 years with an estimated glomerular filtration rate (eGFR) of 30–60 mL/min/1.73 m2 or an eGFR >60 mL/min/1.73 m2 and overt proteinuria who were enrolled in the German Chronic Kidney Disease (GCKD) study. Associations between laboratory, clinical and medication data were assessed.

Results

Intake of several commonly used drugs was independently associated with plasma concentrations of homoarginine and/or related metabolites. Among these, the peroxisome proliferator-activated receptor alpha (PPAR-α) agonist fenofibrate was associated with the most profound differences in ADMA, SDMA and homoarginine plasma concentrations: 66 patients taking fenofibrate had a multivariable adjusted odds ratio (OR) of 5.83 [95% confidence interval (CI) 2.82–12.03, P < 0.001] to have a plasma homoarginine concentration above the median. The median homoarginine plasma concentration in patients taking fenofibrate was 2.30 µmol/L versus 1.55 in patients not taking the drug (P < 0.001). In addition, fibrates were significantly associated with lower plasma SDMA and higher l-arginine concentrations. In contrast, glucocorticoids were associated with lower plasma homoarginine, with adjusted ORs of 0.52 (95% CI 0.40–0.67, P < 0.001) and 0.53 (95% CI 0.31–0.90, P = 0.018) for prednisolone and methylprednisolone, respectively.

Conclusions

In a large cohort of CKD patients, intake of fenofibrate and glucocorticoids were independently associated with higher and lower plasma homoarginine concentrations, respectively. Effects on plasma homoarginine and methylarginines warrant further investigation as potential mechanisms mediating beneficial or adverse drug effects.

Integrated analysis of the Plasmodium species transcriptome

The genome sequence available for different Plasmodium species is a valuable resource for understanding malaria parasite biology. However, comparative genomics on its own cannot fully explain all the species-specific differences which suggests that other genomic aspects such as regulation of gene expression play an important role in defining species-specific characteristics. Here, we developed a comprehensive approach to measure transcriptional changes of the evolutionary conserved syntenic orthologs during the intraerythrocytic developmental cycle across six Plasmodium species. We show significant transcriptional constraint at the mid-developmental stage of Plasmodium species while the earliest stages of parasite development display the greatest transcriptional variation associated with critical functional processes. Modeling of the evolutionary relationship based on changes in transcriptional profile reveal a phylogeny pattern of the Plasmodium species that strictly follows its mammalian hosts. In addition, the work shows that transcriptional conserved orthologs represent potential future targets for anti-malaria intervention as they would be expected to carry out key essential functions within the parasites. This work provides an integrated analysis of orthologous transcriptome, which aims to provide insights into the Plasmodium evolution thereby establishing a framework to explore complex pathways and drug discovery in Plasmodium species with broad host range.

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Comparison of variations in mRNA abundance across six different Plasmodium species.

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Transcriptional conservation and divergence of Plasmodium syntenic orthologs.

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Pattern of Plasmodium transcriptome evolution are established.

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Transcriptionally conserved orthologs represent attractive intervention targets.

Malaria remains a major public health concern despite global efforts in the fight against this disease. The intraerythrocytic stage of the malaria parasites is currently in the spotlight for anti-malarial intervention and vaccine targets. The primary goal of this study is to generate a comprehensive and directly comparable transcriptome dataset across multiple Plasmodium species originating from different hosts. We establish that specific pathways and intraerythrocytic stages are more transcriptionally diverged than others, reflecting transcriptional evolutionary diversity. We further propose a panel of transcriptionally conserved genes as potential drug targets.

A Computational Pipeline for Cross-Species Analysis of RNA-seq Data Using R and Bioconductor

RNA sequencing (RNA-seq) has revolutionized transcriptome analysis through profiling the expression of thousands of genes at the same time. Systematic analysis of orthologous transcripts across species is critical for understanding the evolution of gene expression and uncovering important information in animal models of human diseases. Several computational methods have been published for analyzing gene expression between species, but they often lack crucial details and therefore cannot serve as a practical guide. Here, we present the first step-by-step protocol for cross-species RNA-seq analysis with a concise workflow that is largely based on the free open-source R language and Bioconductor packages. This protocol covers the entire process from short-read mapping, gene expression quantification, differential expression analysis to pathway enrichment. Many useful utilities for data visualization are included. This complete and easy-to-follow protocol provides hands-on guidance for users who are new to cross-species gene expression analysis.

xHeinz: an algorithm for mining cross-species network modules under a flexible conservation model

MOTIVATION

Integrative network analysis methods provide robust interpretations of differential high-throughput molecular profile measurements. They are often used in a biomedical context-to generate novel hypotheses about the underlying cellular processes or to derive biomarkers for classification and subtyping. The underlying molecular profiles are frequently measured and validated on animal or cellular models. Therefore the results are not immediately transferable to human. In particular, this is also the case in a study of the recently discovered interleukin-17 producing helper T cells (Th17), which are fundamental for anti-microbial immunity but also known to contribute to autoimmune diseases.

RESULTS

We propose a mathematical model for finding active subnetwork modules that are conserved between two species. These are sets of genes, one for each species, which (i) induce a connected subnetwork in a species-specific interaction network, (ii) show overall differential behavior and (iii) contain a large number of orthologous genes. We propose a flexible notion of conservation, which turns out to be crucial for the quality of the resulting modules in terms of biological interpretability. We propose an algorithm that finds provably optimal or near-optimal conserved active modules in our model. We apply our algorithm to understand the mechanisms underlying Th17 T cell differentiation in both mouse and human. As a main biological result, we find that the key regulation of Th17 differentiation is conserved between human and mouse.

AVAILABILITY AND IMPLEMENTATION

xHeinz, an implementation of our algorithm, as well as all input data and results, are available at http://software.cwi.nl/xheinz and as a Galaxy service at http://services.cbib.u-bordeaux2.fr/galaxy in CBiB Tools.

CONTACT

gunnar.klau@cwi.nl

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.