Emergent microenvironments of nucleoli

In higher eukaryotes, the nucleolus harbors at least three sub-phases that facilitate multiple functionalities including ribosome biogenesis. The three prominent coexisting sub-phases are the fibrillar center (FC), the dense fibrillar component (DFC), and the granular component (GC). Here, we review recent efforts in profiling sub-phase compositions that shed light on the types of physicochemical properties that emerge from compositional biases and territorial organization of specific types of macromolecules. We highlight roles played by molecular grammars which refers to protein sequence features including the substrate binding domains, the sequence features of intrinsically disordered regions, and the multivalence of these distinct types of domains / regions. We introduce the concept of a barcode of emergent physicochemical properties of nucleoli. Although our knowledge of the full barcode remains incomplete, we hope that the concept prompts investigations into undiscovered emergent properties and engenders an appreciation for how and why unique microenvironments control biochemical reactions

Occurrence of cowpea aphid-borne mosaic virus in peanut in Brazil

Surveys of groundnut crops in northeastern Brazil since 1995 showed the occurrence of a hitherto unreported virus disease. Characteristic leaf symptoms were ring spots and blotches. The virus was seed transmitted in groundnut (1/610) and cowpea (47/796). Local and systemic symptoms were observed in cowpea (cv. TVu 3433) known to be susceptible to most cowpea aphid-borne mosaic virus (CABMV) isolates. The virus was transmitted by aphids Toxoptera citricidus and Aphis gossypii. Using degenerate primers, the 3′ terminal region of the viral genome was cloned and sequenced. Sequence analyses of the coat protein and the 3′ untranslated region indicated that the potyvirus was most closely related to CABMV isolates from South Africa, Zimbabwe, and the United States. On the basis of genome analysis, the virus was identified as CABMV. The natural occurrence of CABMV on groundnut has so far not been reported. The significance of this finding especially for germplasm exchange is discusse

Directed mutational scanning reveals a balance between acidic and hydrophobic residues in strong human activation domains

Acidic activation domains are intrinsically disordered regions of the transcription factors that bind coactivators. The intrinsic disorder and low evolutionary conservation of activation domains have made it difficult to identify the sequence features that control activity. To address this problem, we designed thousands of variants in seven acidic activation domains and measured their activities with a high-throughput assay in human cell culture. We found that strong activation domain activity requires a balance between the number of acidic residues and aromatic and leucine residues. These findings motivated a predictor of acidic activation domains that scans the human proteome for clusters of aromatic and leucine residues embedded in regions of high acidity. This predictor identifies known activation domains and accurately predicts previously unidentified ones. Our results support a flexible acidic exposure model of activation domains in which the acidic residues solubilize hydrophobic motifs so that they can interact with coactivators. A record of this paper\u27s transparent peer review process is included in the supplemental information

Condensates formed by prion-like low-complexity domains have small-world network structures and interfaces defined by expanded conformations

Biomolecular condensates form via coupled associative and segregative phase transitions of multivalent associative macromolecules. Phase separation coupled to percolation is one example of such transitions. Here, we characterize molecular and mesoscale structural descriptions of condensates formed by intrinsically disordered prion-like low complexity domains (PLCDs). These systems conform to sticker-and-spacers architectures. Stickers are cohesive motifs that drive associative interactions through reversible crosslinking and spacers affect the cooperativity of crosslinking and overall macromolecular solubility. Our computations reproduce experimentally measured sequence-specific phase behaviors of PLCDs. Within simulated condensates, networks of reversible inter-sticker crosslinks organize PLCDs into small-world topologies. The overall dimensions of PLCDs vary with spatial location, being most expanded at and preferring to be oriented perpendicular to the interface. Our results demonstrate that even simple condensates with one type of macromolecule feature inhomogeneous spatial organizations of molecules and interfacial features that likely prime them for biochemical activity

Proteomic and functional mapping of cardiac NaV1.5 channel phosphorylation sites

Phosphorylation of the voltage-gated Na+ (NaV) channel NaV1.5 regulates cardiac excitability, yet the phosphorylation sites regulating its function and the underlying mechanisms remain largely unknown. Using a systematic, quantitative phosphoproteomic approach, we analyzed NaV1.5 channel complexes purified from nonfailing and failing mouse left ventricles, and we identified 42 phosphorylation sites on NaV1.5. Most sites are clustered, and three of these clusters are highly phosphorylated. Analyses of phosphosilent and phosphomimetic NaV1.5 mutants revealed the roles of three phosphosites in regulating NaV1.5 channel expression and gating. The phosphorylated serines S664 and S667 regulate the voltage dependence of channel activation in a cumulative manner, whereas the nearby S671, the phosphorylation of which is increased in failing hearts, regulates cell surface NaV1.5 expression and peak Na+ current. No additional roles could be assigned to the other clusters of phosphosites. Taken together, our results demonstrate that ventricular NaV1.5 is highly phosphorylated and that the phosphorylation-dependent regulation of NaV1.5 channels is highly complex, site specific, and dynamic

Transcriptome-wide identification of host genes targeted by tomato spotted wilt virus-derived small interfering RNAs

RNA silencing mechanism functions as a major defense against invading viruses. The caveat in the RNA silencing mechanism is that the effector small interfering RNAs (siRNAs) act on any RNA transcripts with sequence complementarity irrespective of target's origin. A subset of highly expressed viral small interfering RNAs (vsiRNAs) derived from the tomato spotted wilt virus (TSWV; Tospovirus: Bunyaviridae) genome was analyzed for their propensity to downregulate the tomato transcriptome. A total of 11898 putative target sites on tomato transcripts were found to exhibit a propensity for down regulation by TSWV-derived vsiRNAs. In total, 2450 unique vsiRNAs were found to have potential cross-reacting capability with the tomato transcriptome. VsiRNAs were found to potentially target a gamut of host genes involved in basal cellular activities including enzymes, transcription factors, membrane transporters, and cytoskeletal proteins. KEGG pathway annotation of targets revealed that the vsiRNAs were mapped to secondary metabolite biosynthesis, amino acids, starch and sucrose metabolism, and carbon and purine metabolism. Transcripts for protein processing, hormone signalling, and plant-pathogen interactions were the most likely targets from the genetic, environmental information processing, and organismal systems, respectively. qRT-PCR validation of target gene expression showed that none of the selected transcripts from tomato cv. Marglobe showed up regulation, and all were down regulated even upto 20 folds (high affinity glucose transporter). However, the expression levels of transcripts from cv. Red Defender revealed differential regulation as three among the target transcripts showed up regulation (Cc-nbs-lrr, resistance protein, AP2-like ethylene-responsive transcription factor, and heat stress transcription factor A3). Accumulation of tomato target mRNAs of corresponding length was proved in both tomato cultivars using 5′ RACE analysis. The TSWV-tomato interaction at the sRNA interface points to the ability of tomato cultivars to overcome vsiRNA-mediated targeting of NBS-LRR class R genes. These results suggest the prevalence of vsiRNA-induced RNA silencing of host transcriptome, and the interactome scenario is the first report on the interaction between tospovirus genome-derived siRNAs and tomato transcripts, and provide a deeper understanding of the role of vsiRNAs in pathogenicity and in perturbing host machinery

Biomolecular condensates form spatially inhomogeneous network fluids

The functions of biomolecular condensates are thought to be influenced by their material properties, and these will be determined by the internal organization of molecules within condensates. However, structural characterizations of condensates are challenging, and rarely reported. Here, we deploy a combination of small angle neutron scattering, fluorescence recovery after photobleaching, and coarse-grained molecular dynamics simulations to provide structural descriptions of model condensates that are formed by macromolecules from nucleolar granular components (GCs). We show that these minimal facsimiles of GCs form condensates that are network fluids featuring spatial inhomogeneities across different length scales that reflect the contributions of distinct protein and peptide domains. The network-like inhomogeneous organization is characterized by a coexistence of liquid- and gas-like macromolecular densities that engenders bimodality of internal molecular dynamics. These insights suggest that condensates formed by multivalent proteins share features with network fluids formed by systems such as patchy or hairy colloids

A disordered region controls cBAF activity via condensation and partner recruitment

Intrinsically disordered regions (IDRs) represent a large percentage of overall nuclear protein content. The prevailing dogma is that IDRs engage in non-specific interactions because they are poorly constrained by evolutionary selection. Here, we demonstrate that condensate formation and heterotypic interactions are distinct and separable features of an IDR within the ARID1A/B subunits of the mSWI/SNF chromatin remodeler, cBAF, and establish distinct sequence grammars underlying each contribution. Condensation is driven by uniformly distributed tyrosine residues, and partner interactions are mediated by non-random blocks rich in alanine, glycine, and glutamine residues. These features concentrate a specific cBAF protein-protein interaction network and are essential for chromatin localization and activity. Importantly, human disease-associated perturbations in ARID1B IDR sequence grammars disrupt cBAF function in cells. Together, these data identify IDR contributions to chromatin remodeling and explain how phase separation provides a mechanism through which both genomic localization and functional partner recruitment are achieved

Ortervirales: A new viral order unifying five families of reverse-transcribing viruses

Reverse-transcribing viruses, which synthesize a copy of genomic DNA from an RNA template, are widespread in animals, plants, algae and fungi (1, 2).

Predicting Phospholipidosis Using Machine Learning

Phospholipidosis is an adverse effect caused by numerous cationic amphiphilic drugs and can affect many cell types. It is characterized by the excess accumulation of phospholipids and is most reliably identified by electron microscopy of cells revealing the presence of lamellar inclusion bodies. The development of phospholipidosis can cause a delay in the drug development process, and the importance of computational approaches to the problem has been well documented. Previous work on predictive methods for phospholipidosis showed that state of the art machine learning methods produced the best results. Here we extend this work by looking at a larger data set mined from the literature. We find that circular fingerprints lead to better models than either E-Dragon descriptors or a combination of the two. We also observe very similar performance in general between Random Forest and Support Vector Machine models.</p