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We previously piloted the concept of a Connectivity Map (CMap), whereby genes, drugs, and disease states are connected by virtue of common gene-expression signatures. Here, we report more than a 1,000-fold scale-up of the CMap as part of the NIH LINCS Consortium, made possible by a new, low-cost, high-throughput reduced representation expression profiling method that we term L1000. We show that L1000 is highly reproducible, comparable to RNA sequencing, and suitable for computational inference of the expression levels of 81% of non-measured transcripts. We further show that the expanded CMap can be used to discover mechanism of action of small molecules, functionally annotate genetic variants of disease genes, and inform clinical trials. The 1.3 million L1000 profiles described here, as well as tools for their analysis, are available at https://clue.io.

Our thesis is that thin filament function can only be fully understood and muscle regulation then elucidated if atomic structures of the thin filament are available to reveal the positions of tropomyosin on actin in all physiological states. After all, it is tropomyosin influenced by troponin that regulates myosin-crossbridge cycling on actin and therefore controls contraction in all muscles. In addition, we maintain that a complete appreciation of thin filament activation also requires that the mechanical properties of tropomyosin itself are recognized and then related to the effect of myosin-association on actin. Taking the Gestalt-binding of tropomyosin into account, coupled with our electron microscopy structures and computational chemistry, we propose a comprehensive mechanism for tropomyosin regulatory movement over the actin filament surface that explains the cooperative muscle activation process. In fact, well-known point mutations of critical amino acids on the actin–tropomyosin binding interface disrupt Gestalt- binding and are associated with a number of inherited myopathies. Moreover, dysregulation of tropomyosin may also be a factor that interferes with the gatekeeping operation of non-muscle tropomyosin in the controlling interactions of a wide variety of cellular actin-binding proteins. The clinical relevance of Gestalt- binding is discussed in articles by the Marston and the Gunning groups in this special journal issue devoted to the impact of tropomyosin on biological systems. [ABSTRACT FROM AUTHOR]

Using mechanical unfolding by optical tweezers (OT) and steered molecular dynamics (SMD) simulations, we have demonstrated the critical role of Mg2+ ions for the resistance of the Beet Western Yellow Virus (BWYV) pseudoknot (PK) to unfolding. The two techniques were found to be complementary, providing information at different levels of molecular scale. Findings from the OT experiments indicated a critical role of stem 1 for unfolding of the PK, which was confirmed in the SMD simulations. The unfolding pathways of wild type and mutant appeared to depend upon pH and nucleotide sequence. SMD simulations support the notion that the stability of stem 1 is critical for -1 frameshifting. The all-atom scale nature of the SMD enabled clarification of the precise role of two Mg2+ ions, Mg45 and Mg52, as identified in the BWYV X-ray crystallography structure, in -1 franieshifting. On the basis of simulations with "partially" and "fully" hydrated Mg2+ ions, two possible mechanisms of stabilizing stem 1 are proposed. In both these cases Mg2+ ions play a critical role in stabilizing stem 1, either by directly forming a salt bridge between the strands of stem 1 or by stabilizing parallel orientation of the strands in stem 1, respectively. These findings explain the unexpected drop in frameshifting efficiency to null levels of the C8U mutant in a manner consistent with experimental observations. [ABSTRACT FROM AUTHOR]

The rising prevalence of antibiotic resistance threatens human health. While more sophisticated strategies for antibiotic discovery are being developed, target elucidation of new chemical entities remains challenging. In the post-genomic era, expression profiling can play an important role in mechanism-of-action (MOA) prediction by reporting on the cellular response to perturbation. However, the broad application of transcriptomics has yet to fulfill its promise of transforming target elucidation due to challenges in identifying the most relevant, direct responses to target inhibition. We developed an unbiased strategy for MOA prediction, called Perturbation-Specific Transcriptional Mapping (PerSpecTM), in which large-throughput expression profiling of wildtype or hypomorphic mutants, depleted for essential targets, enables a computational strategy to address this challenge. We applied PerSpecTM to perform reference-based MOA prediction based on the principle that similar perturbations, whether chemical or genetic, will elicit similar transcriptional responses. Using this approach, we elucidated the MOAs of three new molecules with activity against Pseudomonas aeruginosa by comparing their expression profiles to those of a reference set of antimicrobial compounds with known MOAs. We also show that transcriptional responses to small molecule inhibition resemble those resulting from genetic depletion of essential targets by CRISPRi by PerSpecTM, demonstrating proof-of-concept that correlations between expression profiles of small molecule and genetic perturbations can facilitate MOA prediction when no chemical entities exist to serve as a reference. Empowered by PerSpecTM, this work lays the foundation for an unbiased, readily scalable, systematic reference-based strategy for MOA elucidation that could transform antibiotic discovery efforts.