Engineering long-range interactions between ultracold atoms with light

Ultracold temperatures in dilute quantum gases opened the way to an exquisite control of matter at the quantum level. Here we focus on the control of ultracold atomic collisions using a laser to engineer their interactions at large interatomic distances. We show that the entrance channel of two colliding ultracold atoms can be coupled to a repulsive collisional channel by the laser light so that the overall interaction between the two atoms becomes repulsive: this prevents them to come close together and to undergo inelastic processes, thus protecting the atomic gases from unwanted losses. We illustrate such an optical shielding mechanism with 39K and 133Cs atoms colliding at ultracold temperature (<1 microkelvin). The process is described in the framework of the dressed-state picture and we then solve the resulting stationary coupled Schrödinger equations. The role of spontaneous emission and photoinduced inelastic scattering is also investigated as possible limitations of the shielding efficiency. We predict an almost complete suppression of inelastic collisions over a broad range of Rabi frequencies and detunings from the 39K D2 line of the optical shielding laser, both within the [0, 200 MHz] interval. We found that the polarization of the shielding laser has a minor influence on this efficiency. This proposal could easily be formulated for other bialkali-metal pairs as their long-range interaction are all very similar to each other.

Trivial Excitation Energy Transfer to Carotenoids Is an Unlikely Mechanism for Non-photochemical Quenching in LHCII

Higher plants defend themselves from bursts of intense light via the mechanism of Non-Photochemical Quenching (NPQ). It involves the Photosystem II (PSII) antenna protein (LHCII) adopting a conformation that favors excitation quenching. In recent years several structural models have suggested that quenching proceeds via energy transfer to the optically forbidden and short-lived S1 states of a carotenoid. It was proposed that this pathway was controlled by subtle changes in the relative orientation of a small number of pigments. However, quantum chemical calculations of S1 properties are not trivial and therefore its energy, oscillator strength and lifetime are treated as rather loose parameters. Moreover, the models were based either on a single LHCII crystal structure or Molecular Dynamics (MD) trajectories about a single minimum. Here we try and address these limitations by parameterizing the vibronic structure and relaxation dynamics of lutein in terms of observable quantities, namely its linear absorption (LA), transient absorption (TA) and two-photon excitation (TPE) spectra. We also analyze a number of minima taken from an exhaustive meta-dynamical search of the LHCII free energy surface. We show that trivial, Coulomb-mediated energy transfer to S1 is an unlikely quenching mechanism, with pigment movements insufficiently pronounced to switch the system between quenched and unquenched states. Modulation of S1 energy level as a quenching switch is similarly unlikely. Moreover, the quenching predicted by previous models is possibly an artifact of quantum chemical over-estimation of S1 oscillator strength and the real mechanism likely involves short-range interaction and/or non-trivial inter-molecular states.

An anionic ligand snap-locks a long-range interaction in a magnesium-folded riboswitch

The archetypical transcriptional crcB fluoride riboswitch from Bacillus cereus is an intricately structured non-coding RNA element enhancing gene expression in response to toxic levels of fluoride. Here, we used single molecule FRET to uncover three dynamically interconverting conformations appearing along the transcription process: two distinct undocked states and one pseudoknotted docked state. We find that the fluoride anion specifically snap-locks the magnesium-induced, dynamically docked state. The long-range, nesting, single base pair A40-U48 acts as the main linchpin, rather than the multiple base pairs comprising the pseudoknot. We observe that the proximally paused RNA polymerase further fine-tunes the free energy to promote riboswitch docking. Finally, we show that fluoride binding at short transcript lengths is an early step toward partitioning folding into the docked conformation. These results reveal how the anionic fluoride ion cooperates with the magnesium-associated RNA to govern regulation of downstream genes needed for fluoride detoxification of the cell.

Dynamic transcriptome and chromatin architecture in granulosa cells during chicken folliculogenesis

Folliculogenesis is a complex biological process involving a central oocyte and its surrounding somatic cells. Three-dimensional chromatin architecture is an important transcription regulator; however, little is known about its dynamics and role in transcriptional regulation of granulosa cells during chicken folliculogenesis. We investigate the transcriptomic dynamics of chicken granulosa cells over ten follicular stages and assess the chromatin architecture dynamics and how it influences gene expression in granulosa cells at three key stages: the prehierarchical small white follicles, the first largest preovulatory follicles, and the postovulatory follicles. Our results demonstrate the consistency between the global reprogramming of chromatin architecture and the transcriptomic divergence during folliculogenesis, providing ample evidence for compartmentalization rearrangement, variable organization of topologically associating domains, and rewiring of the long-range interaction between promoter and enhancers. These results provide key insights into avian reproductive biology and provide a foundational dataset for the future in-depth functional characterization of granulosa cells.

DSResSol: A Sequence-Based Solubility Predictor Created with Dilated Squeeze Excitation Residual Networks

Protein solubility is an important thermodynamic parameter that is critical for the characterization of a protein’s function, and a key determinant for the production yield of a protein in both the research setting and within industrial (e.g., pharmaceutical) applications. Experimental approaches to predict protein solubility are costly, time-consuming, and frequently offer only low success rates. To reduce cost and expedite the development of therapeutic and industrially relevant proteins, a highly accurate computational tool for predicting protein solubility from protein sequence is sought. While a number of in silico prediction tools exist, they suffer from relatively low prediction accuracy, bias toward the soluble proteins, and limited applicability for various classes of proteins. In this study, we developed a novel deep learning sequence-based solubility predictor, DSResSol, that takes advantage of the integration of squeeze excitation residual networks with dilated convolutional neural networks and outperforms all existing protein solubility prediction models. This model captures the frequently occurring amino acid k-mers and their local and global interactions and highlights the importance of identifying long-range interaction information between amino acid k-mers to achieve improved accuracy, using only protein sequence as input. DSResSol outperforms all available sequence-based solubility predictors by at least 5% in terms of accuracy when evaluated by two different independent test sets. Compared to existing predictors, DSResSol not only reduces prediction bias for insoluble proteins but also predicts soluble proteins within the test sets with an accuracy that is at least 13% higher than existing models. We derive the key amino acids, dipeptides, and tripeptides contributing to protein solubility, identifying glutamic acid and serine as critical amino acids for protein solubility prediction. Overall, DSResSol can be used for the fast, reliable, and inexpensive prediction of a protein’s solubility to guide experimental design.

Single Diameter Modulation Effects on Ni Nanowire Array Magnetization Reversal

Geometrically modulated magnetic nanowires are a simple yet efficient strategy to modify the magnetic domain wall propagation since a simple diameter modulation can achieve its pinning during the nanowire magnetization reversal. However, in dense systems of parallel nanowires, the stray fields arising at the diameter interface can interfere with the domain wall propagation in the neighboring nanowires. Therefore, the magnetic behavior of diameter-modulated nanowire arrays can be quite complex and depending on both short and long-range interaction fields, as well as the nanowire geometric dimensions. We applied the first-order reversal curve (FORC) method to bi-segmented Ni nanowire arrays varying the wide segment (45–65 nm diameter, 2.5–10.0 μm length). The FORC results indicate a magnetic behavior modification depending on its length/diameter aspect ratio. The distributions either exhibit a strong extension along the coercivity axis or a main distribution finishing by a fork feature, whereas the extension greatly reduces in amplitude. With the help of micromagnetic simulations, we propose that a low aspect ratio stabilizes pinned domain walls at the diameter modulation during the magnetization reversal. In this case, long-range axial interaction fields nucleate a domain wall at the nanowire extremities, while short-range ones could induce a nucleation at the diameter interface. However, regardless of the wide segment aspect ratio, the magnetization reversal is governed by the local radial stray fields of the modulation near null magnetization. Our findings demonstrate the capacity of distinguishing between complex magnetic behaviors involving convoluted interaction fields.

Competition Between Red Blood Cell Aggregation and Breakup: Depletion Force due to Filamentous Viruses vs. Shear Flow

Human blood is a shear-thinning fluid with a complex response that strongly depends on the red blood cell’s (RBC’s) ability to form aggregates, called rouleaux. Despite numerous investigations, microscopic understanding of the break up of RBC aggregates has not been fully elucidated. Here, we present a study of breaking up aggregates consisting of two RBCs (a doublet) during shear flow. We introduce the filamentous fd bacteriophage as a rod-like depletant agent with a very long-range interaction force, which can be tuned by the rod’s concentration. We visualize the structures while shearing by combining a home-build counter-rotating cone-plate shear cell with microscopy imaging. A diagram of dynamic states for shear rates versus depletant concentration shows regions of different flow responses and separation stages for the RBCs doublets. With increasing interaction forces, the full-contact flow states dominate, such as rolling and tumbling. We argue that the RBC doublets can only undergo separation during tumbling motion when the angle between the normal of the doublets with the flow direction is within a critical range. However, at sufficiently high shear rates, the time spent in the critical range becomes too short, such that the cells continue to tumble without separating.