Acetyl-Phosphate Is Not a Global Regulatory Bridge between Virulence and Central Metabolism in Borrelia burgdorferi

In B. burgdorferi, the Rrp2-RpoN-RpoS signaling cascade is a distinctive system that coordinates the expression of virulence factors required for successful transition between its arthropod vector and mammalian hosts. Rrp2 (BB0763), an RpoN specific response regulator, is essential to activate this regulatory pathway. Previous investigations have attempted to identify the phosphate donor of Rrp2, including the cognate histidine kinase, Hk2 (BB0764), non-cognate histidine kinases such as Hk1, CheA1, and CheA2, and small molecular weight P-donors such as carbamoyl-phosphate and acetyl-phosphate (AcP). In a report by Xu et al., exogenous sodium acetate led to increased expression of RpoS and OspC and it was hypothesized this effect was due to increased levels of AcP via the enzyme AckA (BB0622). Genome analyses identified only one pathway that could generate AcP in B. burgdorferi: the acetate/mevalonate pathway that synthesizes the lipid, undecaprenyl phosphate (C55-P, lipid I), which is essential for cell wall biogenesis. To assess the role of AcP in Rrp2-dependent regulation of RpoS and OspC, we used a unique selection strategy to generate mutants that lacked ackA (bb0622: acetate to AcP) or pta (bb0589: AcP to acetyl-CoA). These mutants have an absolute requirement for mevalonate and demonstrate that ackA and pta are required for cell viability. When the ΔackA or Δpta mutant was exposed to conditions (i.e., increased temperature or cell density) that up-regulate the expression of RpoS and OspC, normal induction of those proteins was observed. In addition, adding 20mM acetate or 20mM benzoate to the growth media of B. burgdorferi strain B31 ΔackA induced the expression of RpoS and OspC. These data suggest that AcP (generated by AckA) is not directly involved in modulating the Rrp2-RpoN-RpoS regulatory pathway and that exogenous acetate or benzoate are triggering an acid stress response in B. burgdorferi

What have proteomics taught us about Leishmania development?

Leishmania are obligatory intracellular parasitic protozoa that cycle between sand fly mid-gut and phagolysosomes of mammalian macrophages. They have developed genetically programmed changes in gene and protein expression that enable rapid optimization of cell function according to vector and host environments. During the last two decades, host-free systems that mimic intra-lysosomal environments have been devised in which promastigotes differentiate into amastigotes axenically. These cultures have facilitated detailed investigation of the molecular mechanisms underlying Leishmania development inside its host. Axenic promastigotes and amastigotes have been subjected to transcriptome and proteomic analyses. Development had appeared somewhat variable but was revealed by proteomics to be strictly coordinated and regulated. Here we summarize the current understanding of Leishmania promastigote to amastigote differentiation, highlighting the data generated by proteomics

Phosfinder: a web server for the identification of phosphate-binding sites on protein structures

Phosfinder is a web server for the identification of phosphate binding sites in protein structures. Phosfinder uses a structural comparison algorithm to scan a query structure against a set of known 3D phosphate binding motifs. Whenever a structural similarity between the query protein and a phosphate binding motif is detected, the phosphate bound by the known motif is added to the protein structure thus representing a putative phosphate binding site. Predicted binding sites are then evaluated according to (i) their position with respect to the query protein solvent-excluded surface and (ii) the conservation of the binding residues in the protein family. The server accepts as input either the PDB code of the protein to be analyzed or a user-submitted structure in PDB format. All the search parameters are user modifiable. Phosfinder outputs a list of predicted binding sites with detailed information about their structural similarity with known phosphate binding motifs, and the conservation of the residues involved. A graphical applet allows the user to visualize the predicted binding sites on the query protein structure. The results on a set of 52 apo/holo structure pairs show that the performance of our method is largely unaffected by ligand-induced conformational changes. Phosfinder is available at http://phosfinder.bio.uniroma2.it

Human lncRNAs harbor conserved modules embedded in different sequence contexts

We analyzed the structure of human long non-coding RNA (lncRNAs) genes to investigate whether the non-coding transcriptome is organized in modular domains, as is the case for protein-coding genes. To this aim, we compared all known human lncRNA exons and identified 340 pairs of exons with high sequence and/or secondary structure similarity but embedded in a dissimilar sequence context. We grouped these pairs in 106 clusters based on their reciprocal similarities. These shared modules are highly conserved between humans and the four great ape species, display evidence of purifying selection and likely arose as a result of recent segmental duplications. Our analysis contributes to the understanding of the mechanisms driving the evolution of the non-coding genome and suggests additional strategies towards deciphering the functional complexity of this class of molecules

Artificial intelligence methods enhance the discovery of RNA interactions

Understanding how RNAs interact with proteins, RNAs, or other molecules remains a challenge of main interest in biology, given the importance of these complexes in both normal and pathological cellular processes. Since experimental datasets are starting to be available for hundreds of functional interactions between RNAs and other biomolecules, several machine learning and deep learning algorithms have been proposed for predicting RNA-RNA or RNA-protein interactions. However, most of these approaches were evaluated on a single dataset, making performance comparisons difficult. With this review, we aim to summarize recent computational methods, developed in this broad research area, highlighting feature encoding and machine learning strategies adopted. Given the magnitude of the effect that dataset size and quality have on performance, we explored the characteristics of these datasets. Additionally, we discuss multiple approaches to generate datasets of negative examples for training. Finally, we describe the best-performing methods to predict interactions between proteins and specific classes of RNA molecules, such as circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs), and methods to predict RNA-RNA or RNA-RBP interactions independently of the RNA type

Autonomous Dissipative Maxwell's Demon in a Diamond Spin Qutrit

Engineered dynamical maps combining coherent and dissipative transformations of quantum states with quantum measurements have demonstrated a number of technological applications, and promise to be a crucial tool in quantum thermodynamic processes. Here we exploit the control on the effective open spin qutrit dynamics of a nitrogen-vacancy center to experimentally realize an autonomous feedback process (Maxwell's demon) with tunable dissipative strength. The feedback is enabled by random measurement events that condition the subsequent dissipative evolution of the qutrit. The efficacy of the autonomous Maxwell's demon is quantified by means of a generalized Sagawa-Ueda-Tasaki relation for dissipative dynamics. To achieve this, we experimentally characterize the fluctuations of the energy exchanged between the system and its the environment. This opens the way to the implementation of a new class of Maxwell's demons, which could be useful for quantum sensing and quantum thermodynamic devices

Restoring brain function after stroke - bridging the gap between animals and humans

Stroke is the leading cause of complex adult disability in the world. Recovery from stroke is often incomplete, which leaves many people dependent on others for their care. The improvement of long-term outcomes should, therefore, be a clinical and research priority. As a result of advances in our understanding of the biological mechanisms involved in recovery and repair after stroke, therapeutic opportunities to promote recovery through manipulation of poststroke plasticity have never been greater. This work has almost exclusively been carried out in preclinical animal models of stroke with little translation into human studies. The challenge ahead is to develop a mechanistic understanding of recovery from stroke in humans. Advances in neuroimaging techniques now enable us to reconcile behavioural accounts of recovery with molecular and cellular changes. Consequently, clinical trials can be designed in a stratified manner that takes into account when an intervention should be delivered and who is most likely to benefit. This approach is expected to lead to a substantial change in how restorative therapeutic strategies are delivered in patients after stroke

The FHP01 DDX3X helicase inhibitor exerts potent anti-tumor activity in vivo in breast cancer pre-clinical models

Inhibition of DDX3X expression or activity reduces proliferation in cells from various tumor tissues, in particular in breast cancer, and its expression often correlates to tumor aggressiveness. This makes DDX3X a prominent candidate for the design of drugs for novel personalized therapeutic strategies. Starting from an in silico drug discovery approach, a group of molecules has been selected by molecular docking at the RNA binding site of DDX3X. Here, the most promising among them, FHP01, was evaluated in breast cancer preclinical models. Specifically, FHP01 exhibited very effective antiproliferative and killing activity against different breast cancer cell types, among which those from triple-negative breast cancer (TNBC). Interestingly, FHP01 also inhibited WNT signaling, a key tumorigenic pathway already correlated to DDX3X functions in breast cancer model cell lines. Ultimately, FHP01 also caused a significant reduction, in vivo, in the growth of MDA MB 231- derived TNBC xenograft models. Importantly, FHP01 showed good bioavailability and no toxicity on normal peripheral blood mononuclear cells in vitro and on several mouse tissues in vivo. Overall, our data suggest that the use of FHP01 and its related compounds may represent a novel therapeutic approach with high potential against breast cancer, including the triple-negative subtype usually correlated to the most unfavorable outcomes because of the lack of available targeted therapies