Large Perturbations Research Articles

Detection of Vertical Changes in the Ionospheric Electron Density Structures by the Radio Occultation Technique Onboard the FORMOSAT-7/COSMIC2 Mission over the Eruption of the Tonga Underwater Volcano on 15 January 2022

A large near-surface perturbation such as the eruption of the Tonga underwater volcano on 15 January 2022 can generate disturbances in the Earth’s atmosphere and ionosphere. It is quite challenging to detect and investigate the disturbances in the vertical direction due to the lack of ground-based instruments, especially in the ocean area. To examine the vertical disturbances due to the Tonga eruption, this study utilizes the radio occultation (RO) technique onboard the satellites of the FORMOSAT-7/COSMIC2 (F7/C2) mission to sound the ionospheric electron density (Ne) profiles in the Central Pacific Ocean area around the eruption. The ionospheric Ne profiles show that the eruption almost annihilated the typical Chapman-layer structure over the eruption in the nighttime on 15 January. The Hilbert–Huang transform was applied to expose the vertical changes in the Ne structures as functions of wavelength and altitude. The analysis shows not only the occurrence of the small-scale disturbances with a wavelength of ~20 km from 100 km to 500 km altitudes, but also the significant attenuation of the structures with a wavelength >50 km, which has never been reported before. The time series of the total electron content from the ground-based Global Navigation Satellite System receiver near the eruption also verifies the significant long-lasting disturbances due to the eruption.

Stability of combination of rarefaction waves with viscous contact wave for compressible Navier-Stokes equations with temperature-dependent transport coefficients and large data

Abstract In this article, we study the large-time behavior of combination of the rarefaction waves with viscous contact wave for a one-dimensional compressible Navier-Stokes system whose transport coefficients depend on the temperature. It is shown that if the adiabatic exponent γ is suitably close to 1, the unique solution global in time to ideal polytropic gas exists and asymptotically tends toward the combination of a viscous contact wave with rarefaction waves under large initial perturbation. New and subtle analysis is developed to overcome difficulties due to the smallness of γ – 1 to derive heat kernel estimates. Moreover, our results extend the studies in a previous work [F. M. Huang, J. Li, and A. Matsumura, Arch. Ration. Mech. Anal. 197 (2010), no. 1, 89–116].

Predicting antibiotic resistance in complex protein targets using alchemical free energy methods.

Drug resistant Mycobacterium tuberculosis, which mostly results from single nucleotide polymorphisms in antibiotic target genes, poses a major threat to tuberculosis treatment outcomes. Relative binding free energy (RBFE) calculations can rapidly predict the effects of mutations, but this approach has not been tested on large, complex proteins. We use RBFE calculations to predict the effects of M. tuberculosis RNA polymerase and DNA gyrase mutations on rifampicin and moxifloxacin susceptibility respectively. These mutations encompass a range of amino acid substitutions with known effects and include large steric perturbations and charged moieties. We find that moderate numbers (n = 3–15) of short RBFE calculations can predict resistance in cases where the mutation results in a large change in the binding free energy. We show that the method lacks discrimination in cases with either a small change in energy or that involve charged amino acids, and we investigate how these calculation errors may be decreased.

Predicting the mutation effects of protein–ligand interactions via end-point binding free energy calculations: strategies and analyses

Protein mutations occur frequently in biological systems, which may impact, for example, the binding of drugs to their targets through impairing the critical H-bonds, changing the hydrophobic interactions, etc. Thus, accurately predicting the effects of mutations on biological systems is of great interests to various fields. Unfortunately, it is still unavailable to conduct large-scale wet-lab mutation experiments because of the unaffordable experimental time and financial costs. Alternatively, in silico computation can serve as a pioneer to guide the experiments. In fact, numerous pioneering works have been conducted from computationally cheaper machine-learning (ML) methods to the more expensive alchemical methods with the purpose to accurately predict the mutation effects. However, these methods usually either cannot result in a physically understandable model (ML-based methods) or work with huge computational resources (alchemical methods). Thus, compromised methods with good physical characteristics and high computational efficiency are expected. Therefore, here, we conducted a comprehensive investigation on the mutation issues of biological systems with the famous end-point binding free energy calculation methods represented by MM/GBSA and MM/PBSA. Different computational strategies considering different length of MD simulations, different value of dielectric constants and whether to incorporate entropy effects to the predicted total binding affinities were investigated to provide a more accurate way for predicting the energetic change upon protein mutations. Overall, our result shows that a relatively long MD simulation (e.g. 100 ns) benefits the prediction accuracy for both MM/GBSA and MM/PBSA (with the best Pearson correlation coefficient between the predicted ∆∆G and the experimental data of ~ 0.44 for a challenging dataset). Further analyses shows that systems involving large perturbations (e.g. multiple mutations and large number of atoms change in the mutation site) are much easier to be accurately predicted since the algorithm works more sensitively to the large change of the systems. Besides, system-specific investigation reveals that conformational adjustment is needed to refine the micro-environment of the manually mutated systems and thus lead one to understand why longer MD simulation is necessary to improve the predicting result. The proposed strategy is expected to be applied in large-scale mutation effects investigation with interpretation.Graphical

Mitigating the effect of errors in source parameters on seismic (waveform) tomography

SUMMARYWe investigate the effect of errors in earthquake source parameters on the tomographic inverse problem and propose mitigation strategies for avoiding artefacts caused by such errors. In global catalogues, mislocation errors can amount to tens of kilometres both horizontally and vertically, while fault plane uncertainties can be of the order of tens of degrees. We conduct a perturbation study investigating both errors in the source location and in the moment tensor. Spatial perturbations of 5 km and fault plane perturbations of 5° result in measured time-shifts of the order of 0.5 to several seconds, which in five iterations lead to artefacts with amplitudes of the order of 0.5–1 per cent spanning up to several hundreds of kilometres. Larger perturbations (e.g. 20 km) lead to artefacts similar in amplitude (∼5 per cent) to the features judged to be interpretable in tomographic models. This can be further exacerbated by the cumulative effect of systematic errors. Mitigation strategies consist of removing a region around the source from the gradient and discarding traces where amplitudes are comparatively small. The most problematic type of error is a horizontal mislocation, because its imprint is not removed by such measures—discarding a ‘suspicious’ event may be the only option if no trustworthy ground truth is available. Although this study focuses on (adjoint) waveform tomography, a large part of the results are equally valid for any other type of imaging method that is based on time- and/or phase-shift measurements. The concerns and mitigation strategies presented here therefore have broader applicability.

Well-posedness of the Riemann problem with two shocks for the isentropic Euler system in a class of vanishing physical viscosity limits

We consider the Riemann problem composed of two shocks for the 1D Euler system. We show that the Riemann solution with two shocks is stable and unique in the class of weak inviscid limits of solutions to the Navier-Stokes equations with initial data with bounded energy. This work extends to the case of two shocks a previous result of the authors in the case of a single shock. It is based on the method of weighted relative entropy with shifts known as a-contraction theory. A major difficulty due to the method is that very little control is available on the shifts. A modification of the construction of the shifts is needed to ensure that the two shock waves are well separated, at the level of the Navier-Stokes system, even when subjected to large perturbations. This work put the foundations needed to consider a large family of interacting waves. It is a key result in the program to solve the Bianchini-Bressan conjecture, that is the inviscid limit of solutions to the Navier-Stokes equation to the unique BV solution of the Euler equation, in the case of small BV initial values.

Robustness of DNA looping across multiple cell divisions in individual bacteria

DNA looping has emerged as a central paradigm of transcriptional regulation, as it is shared across many living systems. One core property of DNA looping-based regulation is its ability to greatly enhance repression or activation of genes with only a few copies of transcriptional regulators. However, this property based on a small number of proteins raises the question of the robustness of such a mechanism with respect to the large intracellular perturbations taking place during growth and division of the cell. Here we address the issue of sensitivity to variations of intracellular parameters of gene regulation by DNA looping. We use the lac system as a prototype to experimentally identify the key features of the robustness of DNA looping in growing Escherichia coli cells. Surprisingly, we observe time intervals of tight repression spanning across division events, which can sometimes exceed 10 generations. Remarkably, the distribution of such long time intervals exhibits memoryless statistics that is mostly insensitive to repressor concentration, cell division events, and the number of distinct loops accessible to the system. By contrast, gene regulation becomes highly sensitive to these perturbations when DNA looping is absent. Using stochastic simulations, we propose that the observed robustness to division emerges from the competition between fast, multiple rebinding events of repressors and slow initiation rate of the RNA polymerase. We argue that fast rebinding events are a direct consequence of DNA looping that ensures robust gene repression across a range of intracellular perturbations.

Methods of Air Traffic Management Using Artificial Intelligence in India

Artificial intelligence (AI) has been recognised as having a broad potential to reduce human workload or increase human capabilities in complex scenarios; however, it is now clear that AI also plays an important role in transforming our lives by promoting more efficient existing services or completely new services. AI is already assisting managers (airlines/airports managers, air traffic management) and operators in a wide range of aviation and air traffic system applications (pilots, air traffic controllers, airport operators, flow controllers). The aviation and air traffic management (ATM) sectors are now confronted with new interconnected challenges: energy transition, increased environmental protection, increased capacity flexibility, integration of new components into air traffic (drones), and system resilience to large traffic perturbations (economic crises, pandemics). AI should help to discover effective solutions to all of these problems. The capacity and safety of the airspace system are heavily reliant on the competent coordination of air traffic control System (ATCS) and flight desk employees. This indicates that aviation traffic will expand at an exponential pace, causing substantial congestion, flight delays, and pollution. Maintaining safe spacing between aircrafts, directing them during takeoff and landing from airports, guiding them around adverse weather, and ensuring that traffic moves smoothly with minimum delays. The goal of this Research Topic is to develop and apply new AI techniques to solve new aircraft operations and air traffic management problems, with the goal of making air transportation operations (including air traffic) more efficient and safe than they are today, while new aviation technologies and new airspace organisation concepts are introduced, and the main goal of this research is to provide automatic communication between the airport and the aircraft. The Problem of manually checking climatic conditions, runway parameters, air traffic, and various other information can be solved by using GSM technology. To reduce the manual efforts and human errors. Before landing, the arrival time of the aircraft is announced automatically.

Insight into the C-terminal SH3 domain mediated binding of Drosophila Drk to Sos and Dos

Drk, a Drosophila homologue of human GRB2, interacts with Sevenless (Sev) receptor via its SH2 domain, while the N- and C-terminal SH3 domains (Drk-NSH3 and Drk-CSH3, respectively) are responsible for the interaction with proline-rich motifs (PRMs) of Son of sevenless (Sos) or Daughter of Sevenless (Dos). Drk-NSH3 on its own has a conformational equilibrium between folded and unfolded states, and the folded state is stabilised by the association with a Sos-derived proline-rich peptide with PxxPxR motif. In contrast, Drk-CSH3 is supposed to bind PxxxRxxKP motifs in Dos. Aiming at clarifying the structural and functional differences between the two SH3 domains, we performed NMR studies of Drk-CSH3. The resulting solution structure and the 15N-relaxation data showed that Drk-CSH3 consists of a stable domain. Large chemical shift perturbation was commonly found around the RT loop and the hydrophobic patch, while there were also changes that occur characteristically for Sos- or Dos-derived peptides. Sos-derived two peptides with PxxPxR motif showed stronger affinity to Drk-CSH3, indicating that the Sos PRMs can bind both N- and C-SH3 domains. Dos-derived two peptides could also bind Drk-CSH3, but with much weaker affinity, suggesting a possibility that any cooperative binding of Dos-PRMs may strengthen the Drk-Dos interaction. The NMR studies as well as the docking simulations provide valuable insights into the biological and biophysical functions of two SH3 domains in Drk.

Unsteady two-phase region evolution of SCO2 centrifugal compressor

In this study, unsteady numerical simulations of centrifugal compressors with and without volute were carried out. The unsteady two-phase region evolution in the centrifugal compressor is obtained. Large coherent perturbations were revealed by the decomposition of the transient flow data using the dynamic mode decomposition (DMD) approach. The results imply that because of the low static pressure strip LP1, the two-phase region presents a triangular distribution at the blade leading edge (LE) of the pressure surface (PS) side in one impeller rotation period for both a low flow rate and the design flow rate. At a high flow rate, the two-phase region displays a double triangle distribution on the PS side of the blade LE, which is correlated with the low static pressure strips LP1 and LP2. The maximum two-phase region on the PS side of the LE of the blade occurs downstream of the LP1 position. The two-phase region in the tip clearance is deflected along the LP1 trajectory. DMD analysis shows that there are four modes related to the two-phase region in the tip clearance: mean flow mode with a frequency of 0 Hz and three modes with frequencies of 0.5, 1.0, and 1.5 BPF respectively. Furthermore, the circumferential local perturbation region of these four modes has the same deflection trajectory as that of LP1.

Effect of clustering on primordial black hole microlensing constraints

Stellar microlensing observations tightly constrain compact object dark matter in the mass range (10-11–103)M ⊙. Primordial Black Holes (PBHs) form clusters, and it has been argued that these microlensing constraints are consequently weakened or evaded. For the most commonly studied PBH formation mechanism, the collapse of large gaussian curvature perturbations generated by inflation, the clusters are sufficiently extended that the PBHs within them act as individual lenses. We find that if the typical mass of the clusters is sufficiently large, ≳ 106 M ⊙, then the event duration distribution can deviate significantly from that produced by a smooth dark matter distribution, in particular at the shortest durations. As a consequence of this, the probability distribution of the number of observed events is non-Poissonian, peaking at a lower value, with an extended tail to large numbers of events. However, for PBHs formed from the collapse of large inflationary perturbations, the typical cluster is expected to contain ∼ 103 PBHs. In this case the effect of clustering is negligibly small, apart from for the most massive PBHs probed by decade-long stellar microlensing surveys (M PBH ∼ 103 M ⊙).

Large-amplitude effects on interface perturbation growth in Richtmyer–Meshkov flows with reshock

Experimental and theoretical studies on the Richtmyer–Meshkov (RM) instability of heavy/light gaseous interfaces with reshock are performed. Both small and large initial perturbation amplitudes of single- and quasi-single-mode interfaces are considered, highlighting the effects of interface amplitude and shape on the linear and nonlinear growths of the RM instability. The results indicate that for small-amplitude interfaces distorted before and after the first reshock arrival, the perturbation growths at linear stages can be well predicted by the impulsive model. For large-amplitude interfaces, however, the reshock acceleration on the evolving interface promotes the mode interaction and enhances the nonlinear effects, making the perturbation growth rates reduced in comparison with those in the singly shocked cases. The complete evolution, especially the bubble evolution, has a strong memory of initial shapes, while for large-amplitude cases, the spike evolution is nearly independent of them owing to the destruction of large-scale vortices and multiple-shock-induced small-scale structures. Compared with that of the single-mode case, the normalized perturbation growths after reshock for the quasi-single-mode cases are more sensitive to initial amplitudes. To better describe the linear growth rates of the RM instability induced by the incident shock and reshock, the reduction factor models for large-amplitude cases are developed, which successfully predict the non-monotonic dependence of linear growth rates on initial perturbation amplitudes. For small-amplitude cases, the nonlinear model proposed for the singly shocked case can predict the reshocked nonlinear growth, while for large-amplitude cases, it is invalid because the perturbation growth shows a linear characteristic after reshock.

Formation of primordial black holes after Starobinsky inflation

In this paper, we adapted the Appleby–Battye–Starobinsky model of [Formula: see text] gravity towards describing double cosmological inflation and formation of primordial black holes with masses up to [Formula: see text] g in the single-field model. We found that it is possible to get an enhancement of the power spectrum of scalar curvature perturbations to the level beyond the Hawking (black hole evaporation) limit of [Formula: see text] g, so that the primordial black holes resulting from gravitational collapse of those large primordial perturbations can survive in the present universe and form part of cold dark matter. Our results agree with the current measurements of cosmic microwave background radiation within [Formula: see text] but require fine-tuning of the parameters.

Baroclinic Instability of a Time-Dependent Zonal Shear Flow

In the real atmosphere, the development of large-scale motion is often related to the baroclinic properties of the atmosphere. So, it is necessary to discuss the stability condition of baroclinic flow. It is advantageous to use a layered model to discuss baroclinic instability, not only to apply the potential vortex equation directly, but also to deal with shear of basic flow. The stability and oscillatory shear ability of Rossby waves are studied based on the two-layer Phillips model in the β plane; then, we summarize the baroclinic instability of time-dependent zonal shear flows. The multiscale method is used to eliminate some terms of natural frequency oscillations of nonlinear operators in the third-order expansion, thus generating an equation about the amplitude of the lowest-order Rossby wave in the long-time variable. The large amplitude perturbation begins to decrease, which produces the desired behavior. After the amplitude decreases for some time, the amplitude of Rossby waves can still be found to oscillate periodically with the time variable.

A Chebyshev Spectral Collocation Method-Based Series Approach for Boundary Layer Flow and Heat Transfer in a Micropolar Fluid past a Permeable Flat Plate

This paper demonstrates the applicability of the large parameter spectral perturbation method (LSPM) to a coupled system of partial differential equations that cannot be solved exactly. The LSPM is a numerical method that employs the Chebyshev spectral collocation method in the solution of a sequence of ordinary differential equations (ODEs) that are derived from decomposing coupled systems of nonlinear partial differential equations (PDEs) using series expansion about a large parameter. The validity of the LSPM is applied to the problem of boundary layer flow and heat transfer in a micropolar fluid past a permeable flat plate in the presence of heat generation and thermal radiation. The coupled nature of the PDEs that define the problem under investigation precludes the option of using series-based methods that seek to generate analytical solutions even in the presence of small or large parameters. The present study demonstrates that the LSPM can easily overcome this limitation while giving very accurate results in a computationally efficient manner. For qualitative validation of the results and the numerical method used, calculations were carried out to graphically obtain the velocity, microrotation, and temperature profiles for selected physical parameter values. The results obtained were found to correlate with the results from a published literature. For quantitative confirmation of our findings, the LSPM numerical solutions were again validated against known results from the literature and against results obtained using the multidomain bivariate spectral quasilinearisation method (MD-BSQLM), and the results were observed to be in perfect agreement. Further accuracy validation is displayed by using residual error and solution error analysis on the governing PDEs and their underlying solutions. This study’s findings indicate that the heat generation and thermal radiation parameters have related effects on the temperature profile, enhancing both the fluid temperature and the thermal boundary layer thickness.

Raman Spectroscopic Studies on Aqueous Sodium Formate Solutions and DFT Calculations

NaHCOO(aq) and NaDCOO(aq) solutions were measured using Raman spectroscopy from dilute to concentrated solutions at 23 °C in water and heavy water from 50 to 4300 cm−1. A concentrated NaHCOO solution in heavy water was also measured. The Raman band parameters of HCOO−(aq) and DCOO−(aq) such as peak position, full width at half maximum (fwhm), integrated intensities, and depolarization values were determined. From the Raman spectroscopic data, it was concluded that the HCOO−(aq) and DCOO−(aq) symmetry is lower than C2v and probably as low as C1. In contrast to the solution state, tt normalsize tt normalsize {text{HCO}}_{2}^{ - } (tt normalsizettnormalsize {text{DCO}}_{2}^{ - }) possess C2v symmetry in the gas phase and the DFT frequencies are given. DFT frequencies on a cluster of HCOO−/DCOO− with five implicit water molecules in the first sphere and placed in a polarizable continuum deviate not more than 1–2% from the measured ones. In the Raman spectrum in NaHCOO(aq), a band doublet at 2730 cm−1 and 2820 cm−1 occurs instead of a single band. The band doublet is due to Fermi resonance and results from the interaction of the overtone of the bending C–H mode, 2ν6 at 1382 cm−1 and ν1. The undisturbed C–H stretching mode, ν1 amounts to 2785 cm−1. In DCOO−(aq), a Fermi doublet was also observed at 2030.5 and 2116.5 cm−1, and the undisturbed wavenumber position amounts to 2101 cm−1. Furthermore, a solution of HCOO− in D2O showed slightly changed frequencies compared with the ones in water caused by the solvent isotope effect. Ion pairing between Na+ and HCOO− characterizes the Raman spectrum at high solute concentrations which are melt-like enabling direct contact between the ions. A NaHCOO solution with high amounts of LiCl added showed large perturbations of the HCOO− bands especially νsCOO− and δ COO− of HCOO−and revealed a stronger affinity of Li+ toward HCOO−. The ion pairs formed are most likely contact ion pairs between Li+ and HCOO− which have different stoichiometry of Li+: HCOO− such as 1:1 and 2:1.Graphical

The Hovering Stability of the Egretta Tail-Sitter VTOL UAV

Vertical takeoff and landing (VTOL) capability has extended the application of unmanned aerial vehicle (UAV) significantly. In this paper, simulation modeling and flight test were employed to investigate the hovering stability of a tail-sitter UAV named Egretta. The hovering stability simulation model was developed based on a simplified rigid body flight dynamic and the time-averaged propeller slipstream flow distribution. Meanwhile, a testing vehicle with PID controllers was built and tested to verify the hovering stability model. It was found that the Egretta UAV can achieve stable hovering in the roll, pitch, and yaw directions. The simulation model has demonstrated accuracy in predicting the hovering stability and dynamic responses with large perturbations in both trend and magnitude. Moreover, the simulation model can be extended to analyze the hovering stability of tail-sitter UAVs with different sizes. The simulation model will be very useful for initial stability sizing and PID optimization investigation.

Abstract 197: A systemic model derivation platform for generating 3D neuroendocrine tumor cell spheroids to accelerate cancer research

Abstract The Broad Cancer Cell Line Factory (CCLF) aims to increase the number and representation of in vitro/ex vivo cell models for common and rare cancer types. Neuroendocrine tumor (NET) cell model derivation is one of the CCLFs focus because it lacks well-characterized, publicly available models.Two major barriers existed in deriving NET cell models, including how to collect sufficient patient tumor tissue samples for the model derivation pilot and how to systematically iterate model derivation strategies since there is no prior knowledge for NET cell model generation success. Thus, we partnered with the MD Anderson Cancer Center, the Dana-Farber Cancer Institute, and the Rare Cancer Research Foundation to collect patient tissue samples. All patient’s NET tissues were sequenced with a targeted Pan-Cancer panel to ensure high tumor content. To reduce fibroblast outgrowth, we combined an empirical rich media matrix (HYBRID technology) with a 3D spheroid culture system to initiate one sample in 16-64 conditions. The growing cultures at passage 3-5 were genomically credentialed to ensure the driver events matched with the original patient tissue. So far, we have received more than 70 NET samples. While several derived models are still under culture, we successfully generated 5 genomically verified NET tumor models, including small intestinal, pancreas, and liver subtypes. To phenotypically characterize these NET models, neuroendocrine biomarkers such as chromogranin A, synaptophysin, SSTR2, and VMAT 1/2 were also evaluated using qRT-PCR and ELISA. We observed that these NET spheroid models display long doubling times (2-4 weeks) at later passages which limits their utility for large scale perturbation experiments and model sharing capability with the research community. While we are currently working on several strategies to improve the propagation ability in these models, 1 (out of 5) model has reached passage 15 with a 3 day doubling time. Genomic studies, such as RNAseq, will be performed to address the model transcriptome changes after overcoming growth plateaus. Here we showed that it is feasible to derive NET models from patient biospecimens using our HYBRID strategy. As we expand our NET cohort, we will further refine disease-specific model generation protocols for different NET types. Our goal is to share our model generation experience and make these tumor cell models publicly available to the research community in order to accelerate cancer research. Citation Format: Adel Attari, Madison Liistro, Barbara Van Hare, Jennifer Chan, Emma Coleman, Tim Heffernan, Bianca Amador, Matthew Meyerson, Jesse Boehm, William Sellers, Yuen-Yi (Moony) Tseng. A systemic model derivation platform for generating 3D neuroendocrine tumor cell spheroids to accelerate cancer research [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 197.

Abstract 1226: A genome wide pharmacological perturbation platform

Abstract Background: Large scale genetic perturbations screens have been instrumental for many key discoveries. In the last decade sequence specific genetic perturbations created RNAi and CRISPR (PMID: 25446316). Recently, specific genome targeting approaches using single guide RNAs (sgRNAs) for the CRISPR-Cas9 system have been repurposed to induce sequence-specific repression or activation of gene expression at a genome-wide scale. Different perturbation approaches have different effects and encompass a trade-off between specificity and duration in establishing a measurable perturbation which can result in different biological readouts. However, bench-side strategies are time consuming and expensive. The method described here aims to build a systems-based computational platform to assess pharmacological and biological perturbations at genome-wide network level.Methods: Our network tool NetDecoder (Nucleic Acids Res. 2016; 44(10):e100) that models genome-wide information flow will be used to build context specific protein-protein interaction networks. These networks will be subsequently subjected to in silico perturbations and their impacts on network properties will be assessed. AVANA and Demeter datasets will be used during method validation procedures. Results: Using publicly available expression datasets we generated context specific Breast Cancer networks and individually manipulated nodes and edges of context-specific networks associated with pharmacological FDA approved targets. Our perturbation networks captured cellular rewiring by engulfing new gene players, alterations of the network size and its connectivity. Conclusions: Our in-silico genome wide perturbation platform provides a flexible approach to fine-tune single and tandem manipulations, allowing for inexpensively monitoring a range of pharmacological interventions using large omics data. Citation Format: Cristina Correia, Choong Yong Ung, Cheng Zhang, Scott H. Kaufmann, Hu Li. A genome wide pharmacological perturbation platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1226.

Differential timing of gene expression and recruitment in independent origins of CAM in the Agavoideae (Asparagaceae).

Crassulacean acid metabolism (CAM) photosynthesis has evolved repeatedly across the plant tree of life, however our understanding of the genetic convergence across independent origins remains hampered by the lack of comparative studies. Here, we explore gene expression profiles in eight species from the Agavoideae (Asparagaceae) encompassing three independent origins of CAM. Using comparative physiology and transcriptomics, we examined the variable modes of CAM in this subfamily and the changes in gene expression across time of day and between well watered and drought-stressed treatments. We further assessed gene expression and the molecular evolution of genes encoding phosphoenolpyruvate carboxylase (PPC), an enzyme required for primary carbon fixation in CAM. Most time-of-day expression profiles are largely conserved across all eight species and suggest that large perturbations to the central clock are not required for CAM evolution. By contrast, transcriptional response to drought is highly lineage specific. Yucca and Beschorneria have CAM-like expression of PPC2, a copy of PPC that has never been shown to be recruited for CAM in angiosperms. Together the physiological and transcriptomic comparison of closely related C3 and CAM species reveals similar gene expression profiles, with the notable exception of differential recruitment of carboxylase enzymes for CAM function.