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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.

Background Unbiased assessment of the risks associated with acquisition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is critical to informing mitigation efforts during pandemics. The objective of our study was to understand the risk factors for acquiring coronavirus disease 2019 (COVID-19) in a large prospective cohort of adult residents in a large US metropolitan area. Methods We designed a fully remote longitudinal cohort study involving monthly at-home SARS-CoV-2 polymerase chain reaction (PCR) and serology self-testing and monthly surveys. Results Between October 2020 and January 2021, we enrolled 10 289 adults reflective of the Boston metropolitan area census data. At study entry, 567 (5.5%) participants had evidence of current or prior SARS-CoV-2 infection. This increased to 13.4% by June 15, 2021. Compared with Whites, Black non-Hispanic participants had a 2.2-fold greater risk of acquiring COVID-19 (hazard ratio [HR], 2.19; 95% CI, 1.91–2.50; P <.001), and Hispanics had a 1.5-fold greater risk (HR, 1.52; 95% CI, 1.32–1.71; P <.016). Individuals aged 18–29, those who worked outside the home, and those living with other adults and children were at an increased risk. Individuals in the second and third lowest disadvantaged neighborhood communities were associated with an increased risk of acquiring COVID-19. Individuals with medical risk factors for severe disease were at a decreased risk of SARS-CoV-2 acquisition. Conclusions These results demonstrate that race/ethnicity and socioeconomic status are the biggest determinants of acquisition of infection. This disparity is significantly underestimated if based on PCR data alone, as noted by the discrepancy in serology vs PCR detection for non-White participants, and points to persistent disparity in access to testing. Medical conditions and advanced age, which increase the risk for severity of SARS-CoV-2 disease, were associated with a lower risk of COVID-19 acquisition, suggesting the importance of behavior modifications. These findings highlight the need for mitigation programs that overcome challenges of structural racism in current and future pandemics. [ABSTRACT FROM AUTHOR]

Background: Antibody response duration following severe acute respiratory syndrome coronavirus 2 infection tends to be variable and depends on severity of disease and method of detection. Study design and methods: COVID‐19 convalescent plasma from 18 donors was collected longitudinally for a maximum of 63–129 days following resolution of symptoms. All the samples were initially screened by the Ortho total Ig test to confirm positivity and subsequently tested with seven additional direct sandwich or indirect binding assays (Ortho, Roche, Abbott, Broad Institute) directed against a variety of antigen targets (S1, receptor binding domain, and nucleocapsid [NC]), along with two neutralization assays (Broad Institute live virus PRNT and Vitalant Research Institute [VRI] Pseudovirus reporter viral particle neutralization [RVPN]). Results: The direct detection assays (Ortho total Ig total and Roche total Ig) showed increasing levels of antibodies over the time period, in contrast to the indirect IgG assays that showed a decline. Neutralization assays also demonstrated declining responses; the VRI RVPN pseudovirus had a greater rate of decline than the Broad PRNT live virus assay. Discussion: These data show that in addition to variable individual responses and associations with disease severity, the detection assay chosen contributes to the heterogeneous results in antibody stability over time. Depending on the scope of the research, one assay may be preferable over another. For serosurveillance studies, direct, double Ag‐sandwich assays appear to be the best choice due to their stability; in particular, algorithms that include both S1‐ and NC‐based assays can help reduce the rate of false‐positivity and discriminate between natural infection and vaccine‐derived seroreactivity. [ABSTRACT FROM AUTHOR]

Striated muscle contraction is regulated by an interaction network connecting the effects of troponin, Ca 2+ , and myosin-heads to the azimuthal positioning of tropomyosin along thin filaments. Many missense mutations, located at the actin–tropomyosin interface, however, reset the regulatory switching mechanism either by weakening or strengthening residue-specific interactions, leading to hyper- or hypo-contractile pathologies. Here, we compute energy landscapes for the actin–tropomyosin interface and quantify contributions of single amino acid residues to actin–tropomyosin binding. The method is a useful tool to assess effects of actin and tropomyosin mutations, potentially relating initial stages of myopathy to alterations in thin filament stability and regulation. Landscapes for mutant filaments linked to hyper-contractility provide a simple picture that describes a decrease in actin–tropomyosin interaction energy. Destabilizing the blocked (relaxed)-state parallels previously noted enhanced Ca 2+ -sensitivity conferred by these mutants. Energy landscapes also identify post-translational modifications that can rescue regulatory imbalances. For example, cardiomyopathy-associated E62Q tropomyosin mutation weakens actin–tropomyosin interaction, but phosphorylation of neighboring S61 rescues the binding-deficit, results confirmed experimentally by in vitro motility assays. Unlike results on hyper-contractility-related mutants, landscapes for tropomyosin mutants tied to hypo-contractility do not present a straightforward picture. These mutations may affect other components of the regulatory network, e.g., troponin–tropomyosin signaling. [ABSTRACT FROM AUTHOR]

Highlights: [•] Head-to-tail linkage is required for tropomyosin cable formation on F-actin. [•] Molecular dynamics of tropomyosin overlap domains were carried out. [•] N- to C-terminal coiled-coils face each other at an orthogonal angle. [•] The bending angle of the overlap domain and the rest of the molecule are comparable. [•] This curvature ensures tropomyosin assembly as an uninterrupted cable on F-actin. [ABSTRACT FROM AUTHOR]

Highlights: [•] An energy landscape was calculated for tropomyosin on the surface of F-actin. [•] The energy minimum locates tropomyosin near its myosin-blocking position on F-actin. [•] Tropomyosin’s myosin-induced open-position is near to the landscape’s energy maximum. [•] Myosin-binding drives tropomyosin uphill over F-actin to activate thin filaments. [•] Mutations distort the energy landscape in ways that explain phenotypic traits. [Copyright &y& Elsevier]

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]

Calcium regulation of cardiac muscle contraction is controlled by the thin-filament proteins troponin and tropomyosin bound to actin. In the absence of calcium, troponin-tropomyosin inhibits myosin-interactions on actin and induces muscle relaxation, whereas the addition of calcium relieves the inhibitory constraint to initiate contraction. Many mutations in thin filament proteins linked to cardiomyopathy appear to disrupt this regulatory switching. Here, we tested perturbations caused by mutant tropomyosins (E40K, DCM; and E62Q, HCM) on intra-filament interactions affecting acto-myosin interactions including those induced further by myosin association. Comparison of wild-type and mutant human α-tropomyosin (Tpm1.1) behavior was carried out using in vitro motility assays and molecular dynamics simulations. Our results show that E62Q tropomyosin destabilizes thin filament off-state function by increasing calcium-sensitivity, but without apparent affect on global tropomyosin structure by modifying coiled-coil rigidity. In contrast, the E40K mutant tropomyosin appears to stabilize the off-state, demonstrates increased tropomyosin flexibility, while also decreasing calcium-sensitivity. In addition, the E40K mutation reduces thin filament velocity at low myosin concentration while the E62Q mutant tropomyosin increases velocity. Corresponding molecular dynamics simulations indicate specific residue interactions that are likely to redefine underlying molecular regulatory mechanisms, which we propose explain the altered contractility evoked by the disease-causing mutations. [ABSTRACT FROM AUTHOR]

Coiled-coil tropomyosin, localized on actin filaments in virtually all eukaryotic cells, serves as a gatekeeper regulating access of the motor protein myosin and other actin-binding proteins onto the thin filament surface. Tropomyosin’s modular pseudo-repeating pattern of approximately 39 amino acid residues is designed to allow binding of the coiled-coil to successive actin subunits along thin filaments. Even though different tropomyosin isoforms contain varying numbers of repeat modules, the pseudo-repeat length, in all cases, matches that of a single actin subunit. Thus, the seven pseudo-repeats of 42 nm long muscle tropomyosin bind to seven successive actin subunits along thin filaments, while simultaneously bending into a super-helical conformation that is preshaped to the actin filament helix. In order to form a continuous cable on thin filaments that is free of gaps, adjacent tropomyosin molecules polymerize head-to-tail by means of a short (∼9 residue) overlap. Several laboratories have engineered peptides to mimic the N- and C-terminal tropomyosin association and to characterize the overlap structure. All overlapping domains examined show a compact N-terminal coiled-coil inserting into a partially opened C-terminal partner, where the opposing coiled-coils at the overlap junction face each other at up to ∼90° twist angles. Here, Molecular Dynamics (MD) simulations were carried out to determine constraints on the formation of the tropomyosin overlap complex and to assess the amount of twisting exhibited by full-length tropomyosin when bound to actin. With the exception of the last 20–40 C- and N-terminal residues, we find that the average tropomyosin structure closely resembles a “canonical” model proposed in the classic work of McLachlan and Stewart, displaying perfectly symmetrical supercoil geometry matching the F-actin helix with an integral number of coiled-coil turns, a coiled-coil helical pitch of 137 Å, a superhelical pitch of 770 Å, and no localized pseudo-rotation. Over the middle 70% of tropomyosin, the average twisting of the coiled-coil deviates only by 10° from the canonical model and the torsional freedom is very small (std. dev. of 7°). This small degree of twisting cannot yield the orthogonal N- and C-termini configuration observed experimentally. In marked contrast, considerable coiled-coil unfolding, splaying and twisting at N- and C-terminal ends is observed, providing the conformational plasticity needed for head-to-tail nexus formation. [Copyright &y& Elsevier]

Abstract: Several approaches have been introduced to interpret, in terms of high-resolution structure, low-resolution structural data as obtained from cryo-EM. As conformational changes are often observed in biological molecules, these techniques need to take into account the flexibility of proteins. Flexibility has been described in terms of movement between rigid domains and between rigid secondary structure elements, which present some limitations for studying dynamical properties. Normal mode analysis has also been used, but is limited to medium resolution data. All-atom molecular dynamics fitting techniques are more appropriate to fit structures into higher-resolution data as full protein flexibility is considered, but are cumbersome in terms of computational time. Here, we introduce a coarse-grained approach; a Go-model was used to represent biological molecules, combined with biased molecular dynamics to reproduce accurately conformational transitions. Illustrative examples on simulated data are shown. Accurate fittings can be obtained for resolution ranging from 5 to 20Å. The approach was also tested on experimental data of Elongation Factor G and Escherichia coli RNA polymerase, where its validity is compared to previous models obtained from different techniques. This comparison demonstrates that quantitative flexible techniques, as opposed to manual docking, need to be considered to interpret low-resolution data. [Copyright &y& Elsevier]

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.

The ability to measure neutralizing antibodies on large scale can be important for understanding features of the natural history and epidemiology of infection, as well as an aid in determining the efficacy of interventions, particularly in outbreaks such as the current severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. Because of the assay's rapid scalability and high efficiency, serology measurements that quantify the presence rather than function of serum antibodies often serve as proxies of immune protection. Here, we report the development of a high-throughput, automated fluorescence-based neutralization assay using SARS-CoV-2 virus to quantify neutralizing antibody activity in patient specimens. We performed large-scale testing of over 19,000 COVID-19 convalescent plasma (CCP) samples from patients who had been infected with SARS-CoV-2 between March and August 2020 across the United States. The neutralization capacity of the samples was moderately correlated with serological measurements of anti-receptor-binding domain (RBD) IgG levels. The neutralizing antibody levels within these convalescent-phase serum samples were highly variable against the original USA-WA1/2020 strain with almost 10% of individuals who had had PCR-confirmed SARS-CoV-2 infection having no detectable antibodies either by serology or neutralization, and ~1/3 having no or low neutralizing activity. Discordance between neutralization and serology measurements was mainly due to the presence of non-IgG RBD isotypes. Meanwhile, natural infection with the earliest SARS-CoV-2 strain USA-WA1/2020 resulted in weaker neutralization of subsequent B.1.1.7 (alpha) and the B.1.351 (beta) variants, with 88% of samples having no activity against the BA.1 (omicron) variant. IMPORTANCE The ability to directly measure neutralizing antibodies on live SARS-CoV-2 virus in individuals can play an important role in understanding the efficacy of therapeutic interventions or vaccines. In contrast to functional neutralization assays, serological assays only quantify the presence of antibodies as a proxy of immune protection. Here, we have developed a high-throughput, automated neutralization assay for SARS-CoV-2 and measured the neutralizing activity of ~19,000 COVID-19 convalescent plasma (CCP) samples collected across the United States between March and August of 2020. These data were used to support the FDA's interpretation of CCP efficacy in patients with SARS-CoV-2 infection and their issuance of emergency use authorization of CCP in 2020.

Tropomyosin regulates a wide variety of actin filament functions and is best known for the role that it plays together with troponin in controlling muscle activity. For effective performance on actin filaments, adjacent 42-nm-long tropomyosin molecules are joined together by a 9- to 10-residue head-to-tail overlapping domain to form a continuous cable that wraps around the F-actin helix. Yet, despite the apparent simplicity of tropomyosin's coiled-coil structure and its well-known periodic association with successive actin subunits along F-actin, the structure of the tropomyosin cable on actin is uncertain. This is because the conformation of the overlap region that joins neighboring molecules is poorly understood, thus leaving a significant gap in our understanding of thin-filament structure and regulation. However, recent molecular-dynamics simulations of overlap segments defined their overall shape and provided unique and sufficient cues to model the whole actin-tropomyosin filament assembly in atomic detail. In this study, we show that these MD structures merge seamlessly onto the ends of tropomyosin coiled-coils. Adjacent tropomyosin molecules can then be joined together to provide a comprehensive model of the tropomyosin cable running continuously on F-actin. The resulting complete model presented here describes for the first time (to our knowledge) an atomic-level structure of αα-striated muscle tropomyosin bound to an actin filament that includes the critical overlap domain. Thus, the model provides a structural correlate to evaluate thin-filament mechanics, self-assembly mechanisms, and the effect of disease-causing mutations., (Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

Muscle contraction is regulated by troponin-tropomyosin, which blocks and unblocks myosin binding sites on actin. To elucidate this regulatory mechanism, the three-dimensional organization of troponin and tropomyosin on the thin filament must be determined. Although tropomyosin is well defined in electron microscopy helical reconstructions of thin filaments, troponin density is mostly lost. Here, we determined troponin organization on native relaxed cardiac muscle thin filaments by applying single particle reconstruction procedures to negatively stained specimens. Multiple reference models led to the same final structure, indicating absence of model bias in the procedure. The new reconstructions clearly showed F-actin, tropomyosin, and troponin densities. At the 25 Å resolution achieved, troponin was considerably better defined than in previous reconstructions. The troponin density closely resembled the shape of troponin crystallographic structures, facilitating detailed interpretation of the electron microscopy density map. The orientation of troponin-T and the troponin core domain established troponin polarity. Density attributable to the troponin-I mobile regulatory domain was positioned where it could hold tropomyosin in its blocking position on actin, thus suggesting the underlying structural basis of thin filament regulation. Our previous understanding of thin filament regulation had been limited to known movements of tropomyosin that sterically block and unblock myosin binding sites on actin. We now show how troponin, the Ca(2+) sensor, may control these movements, ultimately determining whether muscle contracts or relaxes., (Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

A methodology for flexible fitting of all-atom high-resolution structures into low-resolution cryoelectron microscopy (cryo-EM) maps is presented. Flexibility of the modeled structure is simulated by classical molecular dynamics and an additional effective potential is introduced to enhance the fitting process. The additional potential is proportional to the correlation coefficient between the experimental cryo-EM map and a synthetic map generated for an all-atom structure being fitted to the map. The additional forces are calculated as a gradient of the correlation coefficient. During the molecular dynamics simulations under the additional forces, the molecule undergoes a conformational transition that maximizes the correlation coefficient, which results in a high-accuracy fit of all-atom structure into a cryo-EM map. Using five test proteins that exhibit structural rearrangement during their biological activity, we demonstrate performance of our method. We also test our method on the experimental cryo-EM of elongation factor G and show that the model obtained is comparable to previous studies. In addition, we show that overfitting can be avoided by assessing the quality of the fitted model in terms of correlation coefficient and secondary structure preservation.