Fluorochrome Interaction with the Mitochondrial Membrane THE EFFECT OF ENERGY CONSERVATION

Abstract The interaction of 1-anilino-8-naphthalenesulfonate and 6-p-toluidino-2-naphthalenesulfonate with the membrane of both mitochondria and submitochondrial particles was studied. A fluorescence increase of the added fluorochromes was observed when energy was supplied to the membrane of submitochondrial particles, while a fluorescence decrease was observed with intact mitochondria. Binding studies and a comparison of the two fluorochromes have indicated that polarity changes of the membrane are not measured by 1-anilino-8-naphthalenesulfonate and 6-p-toluidino-2-naphthalenesulfonate. The fluorescence changes associated with energy conservation can be attributed to changes in the binding of the fluorochromes. Either a conformational change or a membrane potential change could account for the results

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

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

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

FunClust: a web server for the identification of structural motifs in a set of non-homologous protein structures

The occurrence of very similar structural motifs brought about by different parts of non homologous proteins is often indicative of a common function. Indeed, relatively small local structures can mediate binding to a common partner, be it a protein, a nucleic acid, a cofactor or a substrate. While it is relatively easy to identify short amino acid or nucleotide sequence motifs in a given set of proteins or genes, and many methods do exist for this purpose, much more challenging is the identification of common local substructures, especially if they are formed by non consecutive residues in the sequence

Systemic immunity is required for effective cancer immunotherapy

Immune responses involve coordination across cell types and tissues. However, studies in cancer immunotherapy have focused heavily on local immune responses in the tumor microenvironment. To investigate immune activity more broadly, we performed an organism-wide study in genetically engineered cancer models using mass cytometry. We analyzed immune responses in several tissues after immunotherapy by developing intuitive models for visualizing single-cell data with statistical inference. Immune activation was evident in the tumor and systemically shortly after effective therapy was administered. However, during tumor rejection, only peripheral immune cells sustained their proliferation. This systemic response was coordinated across tissues and required for tumor eradication in several immunotherapy models. An emergent population of peripheral CD4 T cells conferred protection against new tumors and was significantly expanded in patients responding to immunotherapy. These studies demonstrate the critical impact of systemic immune responses that drive tumor rejection

MetaCyto: A Tool for Automated Meta-analysis of Mass and Flow Cytometry Data

While meta-analysis has demonstrated increased statistical power and more robust estimations in studies, the application of this commonly accepted methodology to cytometry data has been challenging. Different cytometry studies often involve diverse sets of markers. Moreover, the detected values of the same marker are inconsistent between studies due to different experimental designs and cytometer configurations. As a result, the cell subsets identified by existing auto-gating methods cannot be directly compared across studies. We developed MetaCyto for automated meta-analysis of both flow and mass cytometry (CyTOF) data. By combining clustering methods with a silhouette scanning method, MetaCyto is able to identify commonly labeled cell subsets across studies, thus enabling meta-analysis. Applying MetaCyto across a set of ten heterogeneous cytometry studies totaling 2,926 samples enabled us to identify multiple cell populations exhibiting differences in abundance between demographic groups

GateFinder: projection-based gating strategy optimization for flow and mass cytometry

Motivation: High-parameter single-cell technologies can reveal novel cell populations of interest, but studying or validating these populations using lower-parameter methods remains challenging.Results: Here, we present GateFinder, an algorithm that enriches high-dimensional cell types with simple, stepwise polygon gates requiring only two markers at a time. A series of case studies of complex cell types illustrates how simplified enrichment strategies can enable more efficient assays, reveal novel biomarkers and clarify underlying biology

Insights into the complex regulation of rpoS in Borrelia burgdorferi

Co-ordinated regulation of gene expression is required for the transmission and survival of Borrelia burgdorferi in different hosts. The sigma factor RpoS (σS), as regulated by RpoN (σ54), has been shown to regulate key virulence factors (e.g. OspC) required for these processes. As important, multiple signals (e.g. temperature, pH, cell density, oxygen) have been shown to increase the expression of σS-dependent genes; however, little is known about the signal transduction mechanisms that modulate the expression of rpoS. In this report we show that: (i) rpoS has a σ54-dependent promoter that requires Rrp2 to activate transcription; (ii) Rrp2Δ123, a constitutively active form of Rrp2, activated σ54-dependent transcription of rpoS/P-lacZ reporter constructs in Escherichia coli; (iii) quantitative reverse transcription polymerase chain reaction (QRT-PCR) experiments with reporter cat constructs in B. burgdorferi indicated that Rrp2 activated transcription of rpoS in an enhancer-independent fashion; and finally, (iv) rpoN is required for cell density- and temperature-dependent expression of rpoS in B. burgdorferi, but histidine kinase Hk2, encoded by the gene immediately upstream of rrp2, is not essential. Based on these findings, a model for regulation of rpoS has been proposed which provides mechanisms for multiple signalling pathways to modulate the expression of the σS regulon in B. burgdorferi