MicroRNAs are important negative regulators of protein-coding gene expression and have been studied intensively over the past years. Several measurement platforms have been developed to determine relative miRNA abundance in biological samples using different technologies such as small RNA sequencing, reverse transcription-quantitative PCR (RT-qPCR) and (microarray) hybridization. In this study, we systematically compared 12 commercially available platforms for analysis of microRNA expression. We measured an identical set of 20 standardized positive and negative control samples, including human universal reference RNA, human brain RNA and titrations thereof, human serum samples and synthetic spikes from microRNA family members with varying homology. We developed robust quality metrics to objectively assess platform performance in terms of reproducibility, sensitivity, accuracy, specificity and concordance of differential expression. The results indicate that each method has its strengths and weaknesses, which help to guide informed selection of a quantitative microRNA gene expression platform for particular study goals.

SummaryWith renewed calls for malaria eradication, next-generation antimalarials need be active against drug-resistant parasites and efficacious against both liver- and blood-stage infections. We screened a natural product library to identify inhibitors of Plasmodium falciparum blood- and liver-stage proliferation. Cladosporin, a fungal secondary metabolite whose target and mechanism of action are not known for any species, was identified as having potent, nanomolar, antiparasitic activity against both blood and liver stages. Using postgenomic methods, including a yeast deletion strains collection, we show that cladosporin specifically inhibits protein synthesis by directly targeting P. falciparum cytosolic lysyl-tRNA synthetase. Further, cladosporin is >100-fold more potent against parasite lysyl-tRNA synthetase relative to the human enzyme, which is conferred by the identity of two amino acids within the enzyme active site. Our data indicate that lysyl-tRNA synthetase is an attractive, druggable, antimalarial target that can be selectively inhibited.

The investigation of interleukin 1β (IL-1β) in human inflammatory diseases is hampered by the fact that it is virtually undetectable in human plasma. We demonstrate that by administering the anti–human IL-1β antibody canakinumab (ACZ885) to humans, the resulting formation of IL-1β–antibody complexes allowed the detection of in vivo–produced IL-1β. A two-compartment mathematical model was generated that predicted a constitutive production rate of 6 ng/d IL-1β in healthy subjects. In contrast, patients with cryopyrin-associated periodic syndromes (CAPS), a rare monogenetic disease driven by uncontrolled caspase-1 activity and IL-1 production, produced a mean of 31 ng/d. Treatment with canakinumab not only induced long-lasting complete clinical response but also reduced the production rate of IL-1β to normal levels within 8 wk of treatment, suggesting that IL-1β production in these patients was mainly IL-1β driven. The model further indicated that IL-1β is the only cytokine driving disease severity and duration of response to canakinumab. A correction for natural IL-1 antagonists was not required to fit the data. Together, the study allowed new insights into the production and regulation of IL-1β in man. It also indicated that CAPS is entirely mediated by IL-1β and that canakinumab treatment restores physiological IL-1β production.

Due to evolutionary conservation of biology, experimental knowledge captured from genetic studies in eukaryotic model organisms provides insight into human cellular pathways and ultimately physiology. Yeast chemogenomic profiling is a powerful approach for annotating cellular responses to small molecules. Using an optimized platform, we provide the relative sensitivities of the heterozygous and homozygous deletion collections for nearly 1800 biologically active compounds. The data quality enables unique insights into pathways that are sensitive and resistant to a given perturbation, as demonstrated with both known and novel compounds. We present examples of novel compounds that inhibit the therapeutically relevant fatty acid synthase and desaturase (Fas1p and Ole1p), and demonstrate how the individual profiles facilitate hypothesis-driven experiments to delineate compound mechanism of action. Importantly, the scale and diversity of tested compounds yields a dataset where the number of modulated pathways approaches saturation. This resource can be used to map novel biological connections, and also identify functions for unannotated genes. We validated hypotheses generated by global two-way hierarchical clustering of profiles for (i) novel compounds with a similar mechanism of action acting upon microtubules or vacuolar ATPases, and (ii) an un-annotated ORF, YIL060w, that plays a role in respiration in the mitochondria. Finally, we identify and characterize background mutations in the widely used yeast deletion collection which should improve the interpretation of past and future screens throughout the community. This comprehensive resource of cellular responses enables the expansion of our understanding of eukaryotic pathway biology.

Large-scale molecular profiling technologies have assisted the identification of disease biomarkers and facilitated the basic understanding of cellular processes. However, samples collected from human subjects in clinical trials possess a level of complexity, arising from multiple cell types, that can obfuscate the analysis of data derived from them. Failure to identify, quantify, and incorporate sources of heterogeneity into an analysis can have widespread and detrimental effects on subsequent statistical studies.We describe an approach that builds upon a linear latent variable model, in which expression levels from mixed cell populations are modeled as the weighted average of expression from different cell types. We solve these equations using quadratic programming, which efficiently identifies the globally optimal solution while preserving non-negativity of the fraction of the cells. We applied our method to various existing platforms to estimate proportions of different pure cell or tissue types and gene expression profilings of distinct phenotypes, with a focus on complex samples collected in clinical trials.We tested our methods on several well controlled benchmark data sets with known mixing fractions of pure cell or tissue types and mRNA expression profiling data from samples collected in a clinical trial. Accurate agreement between predicted and actual mixing fractions was observed. In addition, our method was able to predict mixing fractions for more than ten species of circulating cells and to provide accurate estimates for relatively rare cell types (<10% total population). Furthermore, accurate changes in leukocyte trafficking associated with Fingolomid (FTY720) treatment were identified that were consistent with previous results generated by both cell counts and flow cytometry. These data suggest that our method can solve one of the open questions regarding the analysis of complex transcriptional data: namely, how to identify the optimal mixing fractions in a given experiment.